38th week of 2014 patent applcation highlights part 205 |
Patent application number | Title | Published |
20140279705 | COMPUTER PROGRAM, SYSTEM, AND METHOD FOR MAPPING SOCIAL SECURITY CLAIMING STRATEGIES - A non-transitory computer readable medium having a computer program stored thereon for directing operation of a processor. The computer program receives personal and financial data for a couple; accesses data for a plurality of Social Security claiming strategies for the couple based on the personal and financial data; and illustrates on a graphical display which of the Social Security claiming strategies would provide the maximum present value of benefits for multiple mortality combinations of the couple so that the couple or an advisor for the couple can quickly ascertain which claiming strategy would provide the maximum benefits for a particular mortality combination. | 2014-09-18 |
20140279706 | PRINT-ON-DEMAND AUTHORIZATION AND RETRIEVAL FOR THIRD PARTY PRINT SHOPS USING STANDARDIZED TWO-DIMENSIONAL BARCODE LOOK-UP - A method for managing printing a hard copy of a work from a digital copy of the work, including the steps of a content provider of the digital copy of the work dynamically generating a standardized two-dimensional barcode when the digital copy of the work is produced for a user acquiring rights to the digital copy of the work, the barcode containing a unique URL of the content provider and being embedded in a portion of the digital copy of the work where digital rights management protection is omitted; and a print shop scanning the barcode from the digital copy of the work provided by the user to be readily linked to the content provider, and obtaining authorization and royalty information for printing the hard copy of the work for the user. | 2014-09-18 |
20140279707 | SYSTEM AND METHOD FOR VEHICLE DATA ANALYSIS - The described embodiments relate to systems, methods and computer readable media for determining compliance with recommendations. The systems and methods may involve generating a vehicle recommendation; transmitting the vehicle recommendation to at least one output device, wherein the at least one output device communicates the vehicle recommendation to one or more users; collecting vehicle telemetry data from a vehicle sensor device located in a vehicle, wherein the vehicle sensor device is coupled to one or more vehicle sensors; and determining compliance data based on the vehicle recommendation and the vehicle telemetry data, wherein the compliance data indicates compliance with the recommended vehicle action. The compliance data may be used to determine service rates and/or service level coverage for users. | 2014-09-18 |
20140279708 | SYSTEMS AND METHODS FOR DETERMINING THE TIME TO BUY OR SELL A VEHICLE - Systems and methods for assisting a vehicle owner in making decisions regarding when to replace a vehicle by determining a vehicle owner's satisfaction with the vehicle relative to the cost of owning the vehicle. In one embodiment, a system is configured to provide a model for owner satisfaction which is based on historical vehicle replacement information, but is tailored to a particular owner according to user input. An owner satisfaction curve is produced from this model and is compared to a cost-of-ownership curve that is tailored to the vehicle and possibly also the user. The owner satisfaction curve is compared to the cost-of-ownership curve to enable the user to determine where the cost of ownership exceeds the owner's satisfaction, and the vehicle should be replaced. | 2014-09-18 |
20140279709 | SYSTEMS AND METHODS FOR DETERMINING COSTS OF VEHICLE REPAIRS AND TIMES TO MAJOR REPAIRS - Systems, methods and computer program products for determining costs of vehicle repairs and times to major repairs. In one embodiment, a system includes a computer processor, a data storage device, and an output device. The processor receives information from a user identifying a vehicle of interest. The processor retrieves repair data items that have characteristics common to the vehicle of interest from a database stored in the data storage device. The processor determines repairs that are expected to be necessary for the vehicle of interest based on the retrieved repair data items, and determines the costs associated with the identified expected repairs. The processor provides output to the user indicating the repair costs and/or the times at which the repairs are likely to be necessary. The output may be in graphical and/or numerical form. | 2014-09-18 |
20140279710 | SYSTEM, METHOD AND INTERFACE FOR COMPILED LITERARY WORK - A system, method and interface for compiling literary works from specialized databases and/or from unique interfaces is provided, including a custom database compiled from plural existing literary indexes, wherein a master index is harmonized from said existing indexes according to common terms (e.g., book, chapter and verse for biblical indexes) with deleted duplicates. In exemplary embodiments, the master index is also augmented by ingestion of additional literary works in digital form that are chopped up based on said common terms (e.g., book, chapter, verse) extracted from the literary work. | 2014-09-18 |
20140279711 | VISUALIZING ENERGY CONSUMPTION AND COST TRENDS USING VIRTUAL BILLING CYCLE CALCULATIONS AND STATISTICAL ANALYSIS - A utility consumption information system establishes a virtual billing cycle to enable a user to calculate a bill-to-date cost of utility service related to a certain site without waiting for a utility bill sent from an associated utility service provider. The utility consumption information system provides utility consumption information to a user in an informative user interface and enables the user to monitor utility consumption associated with the site. Moreover, the utility consumption information system allows the user to compare the utility consumption of the site with one or more references, and thus assists the user to determine whether a change in the utility consumption is due to an external factor or an internal factor. | 2014-09-18 |
20140279712 | UTILITY MONITORING AND BILLING SYSTEMS, AND METHODS - Methods and systems using the method of calculating and charging for utility usage are disclosed. The method comprises the steps of, on a processing unit, obtaining a utility bill from a utility company for a multi-unit property, obtaining a reading from at least one submeter monitoring the usage of the utility for each unit of the multi-unit property, totaling the submetered usage, calculating a percent usage of the utility for each unit, calculating a charge for each unit based on the percentage usage for each unit, and billing each unit for the charge calculated for that unit. | 2014-09-18 |
20140279713 | AUTOMATED PAYMENT FOR A RENTAL PERIOD BASED ON DETERMINING THE LOCATION OF A RENTER'S MOBILE COMMUNICATION DEVICE - Systems, apparatus, methods and computer programs provide for self-service rental of rental items. The self-service aspect of the invention allows for renters to obtain the rental, leave the rental agency facility, return the rental item and pay for the rental without having to come into contact with anyone at the rental agency. The invention implements a renter's mobile device. In this regard, the mobile device receives information related to the rental item that the renter desires to rent and initiates the self-service process. The rental period is defined by the time at which the mobile device, equipped with location-determining mechanisms, departs a designated rental area and the time at which the mobile device returns to the same or another designated rental area. Once the rental period is known, the rental period payment amount can be determined based on a predetermined rental rate and payment provided. | 2014-09-18 |
20140279714 | ON-SITE FARM-TO-TABLE RESTAURANT WITH ON-DEMAND HARVESTING - Provided is a restaurant comprising a garden, where a food ingredient of an item served in the restaurant is harvested from the garden after a customer orders the item. Also provided is a restaurant that serves an ingredient to a customer before the ingredient is harvested. Additionally provided is a restaurant that offers an item that has an ingredient that is harvested within six hours of the item being served to a customer. | 2014-09-18 |
20140279715 | LIVE FOOD INGREDIENTS HARVESTED ON-DEMAND - Provided is a restaurant comprising a garden, where a food ingredient of an item served in the restaurant is removed from the garden after a customer of the restaurant orders the item, wherein the food ingredient is part of a plant grown in the garden. Also provided is a restaurant that comprises (a) a garden, and (b) a menu listing at least one item that has an ingredient that is part of a plant in the garden and is removed from the garden after the item is ordered, wherein the ingredient is part of a plant. Additionally provided is a method of selling a food by a food vendor. The method comprises selling the food growing in a container. | 2014-09-18 |
20140279716 | SYSTEMS AND METHODS FOR CLASSIFYING ELECTRONIC INFORMATION USING ADVANCED ACTIVE LEARNING TECHNIQUES - Systems and methods for classifying electronic information or documents into a number of classes and subclasses are provided through an active learning algorithm. In certain embodiments, seed sets may be eliminated by merging relevance feedback and machine learning phases. In certain embodiments, the active learning algorithm forks a number of classification paths corresponding to predicted user coding decisions for a selected document. The active learning algorithm determines an order in which the documents of the collection may be processed and scored by the forked classification paths. Such document classification systems are easily scalable for large document collections, require less manpower and can be employed on a single computer, thus requiring fewer resources. Furthermore, the classification systems and methods described can be used for any pattern recognition or classification effort in a wide variety of fields. | 2014-09-18 |
20140279717 | NETWORK OF INTELLIGENT MACHINES - A network of apparatuses that characterizes items is presented. A self-updating apparatus includes a processing unit that has a memory storing parameters that are useful for characterizing different items, and a processing module configured to automatically select sources from which to receive data, modify the parameters based on the data that is received, and to select recipients of modified parameters. Selection of sources and recipients is based on comparison of parameters between the processing module and the sources, and between the processing module and the recipients, respectively. The processing unit may include an artificial intelligence program (e.g., a neural network such as a machine learning program). When used in a network, the processing units may “train” other processing units in the network such that the characterization accuracy and range of each processing unit improves over time. | 2014-09-18 |
20140279718 | Machine Assisted Troubleshooting of a Customer Support Issue - A knowledge interface is provided that interacts with a user to identify a solution to a customer problem or issue with respect to a particular product or service. The knowledge interface includes data processing functionality configured to dynamically generate a number of components that are presented in at least one display window for display to the user. The components include first data identifying a set of predetermined symptoms linked to the problem or issue and related interface elements for classification of the set of predetermined symptoms, second data identifying a set of predetermined root causes linked to the set of predetermined symptoms and related interface elements for classification of the set of predetermined root causes, and third data identifying a set of solutions linked to the set of predetermined root causes. The third data identifies a best solution based upon the predetermined root causes and their associated class designations. | 2014-09-18 |
20140279719 | VALUE OF INFORMATION WITH STREAMING EVIDENCE - The subject disclosure is directed towards processing evidence, which may include high-dimensional streaming evidence, into a future belief state. The existing evidence is used to project a belief about a future state. The future belief state may be used to determine whether to wait for additional evidence, or to act now without waiting for additional evidence, e.g., based on a cost of the delay. For example, an autonomous assistant may decide based upon the belief whether to engage a person or not, or to wait for more information before the engagement decision is made. | 2014-09-18 |
20140279720 | SYSTEM AND METHOD OF EVENT PUBLICATION IN A GOAL ACHIEVEMENT PLATFORM - Disclosed herein is system, method and architecture facilitating goal setting and achievement and providing positive social and economic motivators for goal achievement. Progress toward a goal is tracked and a determination may be made based the progress whether or not to initiate one or more actions to stimulate progress and/or increase the likelihood of success in achieving a goal and/or achieving a milestone in a path of progression toward the goal. | 2014-09-18 |
20140279721 | LEARNING HEALTH SYSTEMS AND METHODS - A learning health system and associated methods are provided. Biochemical assays are conducted at scheduled intervals on blood samples taken from an individual to provide, for each of a plurality of biochemical parameters, a time series of values representing the individual. Clinical parameters associated with the individual are extracted from a knowledge base. Genomic parameters are determined for the individual. An expected time series is calculated for each of a plural subset of the plurality of biochemical parameters from at least the clinical parameters and the genomic parameters. For each of the plural subset of biochemical parameters, the time series of values representing the individual is compared to the calculated expected time series to determine a likelihood of each of a plurality of conditions for the individual. The likelihood of at least one of the plurality of conditions is communicated to a user. | 2014-09-18 |
20140279722 | METHODS AND SYSTEMS FOR INFERRING USER ATTRIBUTES IN A SOCIAL NETWORKING SYSTEM - A method and system for inferring user attributes in a social networking system. The method includes maintaining a social graph comprising a plurality of nodes and a plurality of edges between the nodes. An unknown, incomplete, or inaccurate user attribute for a user is identified, and a plurality of probability lists are generated using a corresponding plurality of probability algorithms that utilize known user attributes and the social graph. The probability lists include a set of probability entries, each including a prediction we value for the unknown, incomplete, or inaccurate user attribute and a confidence score. Using the probability lists and a plurality of weights corresponding to the probability algorithms, an inferred user attribute value is generated and stored. The weights may be adjusted based upon learning the correct value of the unknown, incomplete, or inaccurate user attribute, and search results may be modified to include the user for search queries seeking information about the inferred user attribute. | 2014-09-18 |
20140279723 | MOBILE DEVICE WITH PREDICTIVE ROUTING ENGINE - Some embodiments of the invention provide a mobile device with a novel route prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for the device's user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. The device's prediction engine only relies on user-specific data stored on the device in some embodiments, relies only on user-specific data stored outside of the device by external devices/servers in other embodiments, and relies on user-specific data stored both by the device and by other devices/servers in other embodiments. | 2014-09-18 |
20140279724 | TAXONOMY CONFIGURATION FOR PAGE ANALYTICS AND CAMPAIGN CREATION - A system for creating and using a universal tag to gather consumer data from a website for the purposes of targeted advertising is provided. The universal tag system has two main subsystems. The first subsystem is a configuration system that is used to define the consumer data to be collected from the website and to define taxonomy and transformation rules to be applied to the collected consumer data. The second subsystem is a runtime system that runs a universal tag client-side script, which is triggered when a consumer lands on a webpage of the website, for collecting the defined consumer data. The runtime system then applies the transformation rules to the collected data and updates a user profile corresponding to the consumer with the transformed data. As well, the runtime system applies the taxonomy rules to the collected data and categorizes the consumer for the purposes of subsequent targeted advertising. | 2014-09-18 |
20140279725 | RADIATION THERAPY PLANING USING INTEGRATED MODEL - System and method for automatically generate therapy plan parameters by use of an integrate model with extended applicable regions. The integrated model integrates multiple predictive models from which a suitable predictive model can be selected automatically to perform prediction for a new patient case. The integrated model may operate to evaluate prediction results generated by each predictive model and the associated prediction reliabilities and selectively output a satisfactory prediction. Alternatively, the integrated model may select a suitable predictive model by a decision hierarchy in which each level corresponds to divisions of a patient data feature set and divisions on a subordinate level are nested with divisions on a superordinate level. | 2014-09-18 |
20140279726 | COMPUTING SYSTEM WITH ITERATIVE KNOWLEDGE MANAGEMENT MECHANISM AND METHOD OF OPERATION THEREOF - A computing system includes: a control unit configured to operate a knowledge discovery component to extract knowledge from data, operate a knowledge engineering component to perform a knowledge extension or a knowledge evolution on the data or the knowledge; and a user interface, coupled to the communication unit, configured to operate an interface component to interact with the knowledge discovery component and the knowledge engineering component. | 2014-09-18 |
20140279727 | Sparse Factor Analysis for Analysis of User Content Preferences - A mechanism for discerning user preferences for categories of provided content. A computer receives response data including a set of preference values that have been assigned to content items by content users. Output data is computed based on the response data using a latent factor model. The output data includes at least: an association matrix that defines K concepts associated with the content items, wherein K is smaller than the number of the content items, wherein, for each of the K concepts, the association matrix defines the concept by specifying strengths of association between the concept and the content items; and a concept-preference matrix including, for each content user and each of the K concepts, an extent to which the content user prefers the concept. The computer may display a visual representation of the association strengths in the association matrix and/or the extents in the concept-preference matrix. | 2014-09-18 |
20140279728 | System and Method for Caring for a Person Afflicted with Dementia - A method of preparing a customized schedule of activities for a person afflicted with dementia, the method comprising (a) prompting a user with questions regarding the person's preferred activities, (b) compiling user responses regarding the person's preferred activities, (c) prompting a user with question concerning the person's ability to perform certain tasks, (d) compiling user responses regarding the person's abilities, (e) determining the person's stage of dementia based on the user responses regarding the person's abilities, and (f) based on the stage of dementia, generating a schedule of activities, the schedule of activities including essential activities and preferred activities, wherein time allocated between the essential and preferred activities in the schedule differs for different stages, and wherein the preferred activities depends at least in part on the responses received in step (b). | 2014-09-18 |
20140279729 | METHODS AND APPARATUS FOR ENTITY DETECTION - Techniques for entity detection include matching a token from at least a portion of a text string with a matching concept in an ontology, wherein the at least a portion of the text string has been labeled as corresponding to a particular entity type. A first concept may be identified as being hierarchically related to the matching concept within the ontology, and a second concept may be identified as being hierarchically related to the first concept within the ontology. Based at least in part on the labeling of the at least a portion of the text string as corresponding to the particular entity type, a statistical model may be trained to associate the first concept with a first probability of corresponding to the particular entity type and the second concept with a second probability of corresponding to the particular entity type. | 2014-09-18 |
20140279730 | IDENTIFYING SALIENT ITEMS IN DOCUMENTS - A set of representations of item-page pairs of items and respective web pages that include the respective items is obtained, each representation including feature function values indicating weights associated with features of associated web pages, the features including page classification features. An annotated set of labeled training data that is annotated with salience annotation values of items for respective web pages that include the items is obtained. The salience annotation values are determined based on a soft function, by determining a first count of a total number of user queries associated with corresponding visits to the respective web pages, and determining a ratio of a second count to the first count, the second count determined as a cardinality of a subset of the corresponding visits that are associated with user queries that include the item, the subset included in the corresponding visits. Models are trained using the annotated set. | 2014-09-18 |
20140279731 | System and Method for Automated Text Coverage of a Live Event Using Structured and Unstructured Data Sources - A system for providing text coverage of a live event, comprising one or more computing devices configured to receive information from one or more structured data sources and from one or more unstructured data sources, and to output information derived therefrom in a periodically updated timeline; a game data processing system comprising a system for deriving data and a story generation system; a social media processing system; and a data source mixing system. A detailed specific example of an embodiment is disclosed in which the live event is a basketball game. | 2014-09-18 |
20140279732 | System for categorizing lists of words of arbitrary origin - The present disclosure provides for categorization of lists of words. The method comprises querying DBpedia to find the resources related to the given list of words. Once the resources are found, the corresponding media Wikipedia categories can be retrieved, as well as their ancestors, generating a graph of categories. A number of graph analysis algorithms can then be applied to the graph, each returning a selected category. For each algorithm a classifier is trained to decide whether the output of the algorithm is indeed the “best” category. An ensemble weighted majority voting can then be used to select the best category based on votes cast by each classifier. The disclosure demonstrates a more accurate selection of the best category and can include an ensemble majority rated voting algorithm comprising all voting members initially casting one vote; i.e., highest frequency, most frequently occurring word, least common ancestor and centrality measures. | 2014-09-18 |
20140279733 | COMPUTER-BASED METHOD AND SYSTEM FOR PROVIDING ACTIVE AND AUTOMATIC PERSONAL ASSISTANCE USING A ROBOTIC DEVICE/PLATFORM - A method and a system for providing personal assistance in daily activities. A method and a system for actively and automatically providing personal assistance, using a robotic device/platform, based on detected data regarding a user and the user's environment. The method and system may include a processor, at least one sensor, an output device, a communications unit, and a database. The database may further include a memory and cloud-based database and computing. The method and system may provide assistance in jogging the memory of the user, parental control of a child, hazard detection, and various other circumstances. The method and system may actively and automatically provide personal assistance regarding health, exercise, diet, or nutrition. The method and system may assist the user or a health professional in health diagnosis and treatment. | 2014-09-18 |
20140279734 | Performing Cross-Validation Using Non-Randomly Selected Cases - A technique to perform cross-validation using a set of randomly selected labeled cases and a set of non-randomly selected labeled cases. A training set for use during cross-validation can include cases from both sets. A test set for use during cross-validation can include cases from the randomly selected set but exclude cases from the non-randomly selected set. | 2014-09-18 |
20140279735 | PROCESS MODEL GENERATED USING BIASED PROCESS MINING - Embodiments relate to a method, system, and computer program product for a process model. The method includes extracting data associated with a process execution trace of a running process and extracting any prior knowledge data relating to the running process. The method also includes calculating at least one transition confidence parameter for the prior knowledge data; and identifying any existing process models relating to the running process. A confidence trace bias is also generated for any existing process model identified. An enhanced bias value is then calculated by combining the confidence trace bias value and value of the transition confidence parameter. Using as input the extracted process execution trace data, the prior knowledge data, the identified existing model and the enhanced bias value, a learned process model is then generated. | 2014-09-18 |
20140279736 | METHOD AND SYSTEM FOR MAPPING SHORT TERM RANKING OPTIMIZATION OBJECTIVE TO LONG TERM ENGAGEMENT - Method, system, and programs for identifying a target metric. In one example, at least one first type of metric computed based on a first period associated with a first length of time is measured for each of a plurality of users. At least one second type of metric computed based on a second period associated with a second length of time is measured for each of the plurality of users. The second length of time is larger than the first length of time. Correlations between each of the at least one first type of metric and each of the at least one second type of metrics are computed with respect to the plurality of users. A target metric is identified from the at least one first type of metric based on the correlations. The target metric is correlated with the at least one second type of metric. | 2014-09-18 |
20140279737 | MONTE-CARLO APPROACH TO COMPUTING VALUE OF INFORMATION - The subject disclosure is directed towards the use of Monte Carlo (MC) procedures for computing the value of information (VOI), including with long evidential sequences. An MC-VOI algorithm is used to output a decision as to balancing the value and costs of collecting information in advance of taking action by running prediction model-based simulations to determine execution paths through possible states, and processing the results of the simulations/paths taken into a final decision. | 2014-09-18 |
20140279738 | Non-Linear Classification of Text Samples - Non-linear classifiers and dimension reduction techniques may be applied to text classification. Non-linear classifiers such as random forest, Nyström/Fisher, and others, may be used to determine criteria usable to classify text into one of a plurality of categories. Dimension reduction techniques may also be used to reduce feature space size. Machine learning techniques may be used to develop criteria (e.g., trained models) that can be used to automatically classify text. Automatic classification rates may be improved and result in fewer numbers of text samples being unclassifiable or being incorrectly classified. User-generated content may be classified, in some embodiments. | 2014-09-18 |
20140279739 | RESOLVING AND MERGING DUPLICATE RECORDS USING MACHINE LEARNING - According to various embodiments of the present invention, an automated technique is implemented for resolving and merging fields accurately and reliably, given a set of duplicated records that represents a same entity. In at least one embodiment, a system is implemented that uses a machine learning (ML) method, to train a model from training data, and to learn from users how to efficiently resolve and merge fields. In at least one embodiment, the method of the present invention builds feature vectors as input for its ML method. In at least one embodiment, the system and method of the present invention apply Hierarchical Based Sequencing (HBS) and/or Multiple Output Relaxation (MOR) models in resolving and merging fields. Training data for the ML method can come from any suitable source or combination of sources. | 2014-09-18 |
20140279740 | METHOD AND APPARATUS FOR DETECTION AND PREDICTION OF EVENTS BASED ON CHANGES IN BEHAVIOR - A computer-implemented process for detecting and predicting events occurring to a person, includes: observing, using a sensor, a reading of a parameter of a body part of the person which is one of: horizontal location, vertical height, orientation, velocity, and time of observation, wherein the reading corresponds to less information than needed to define the person's posture; receiving the reading into a computer memory; determining from the received reading a pattern of behavior; detecting a change in behavior; identifying from the change in behavior a combination of one or more readings corresponding to an abnormal event; and producing an alert signal when the combination of one or more readings corresponding to the abnormal event is identified. The process may be practiced using a computing machine including a computer memory; a sensor; and a computer processor. | 2014-09-18 |
20140279741 | SCALABLE ONLINE HIERARCHICAL META-LEARNING - A method of meta-learning includes receiving a prediction objective, extracting a plurality of subsets of data from a distributed dataset, generating a plurality of local predictions, wherein each local prediction is based on a different subset of the plurality of subsets of data and the prediction objective, combining the plurality of local predictions, and generating a final prediction based on the combined local predictions. | 2014-09-18 |
20140279742 | DETERMINING AN OBVERSE WEIGHT - A technique for determining an obverse weight. A set of cases can be divided into bins. An obverse weight for a bin can be determined based on an importance weight of the bin and a variance of an error estimate of the bin. | 2014-09-18 |
20140279743 | JABBA-TYPE OVERRIDE FOR CORRECTING OR IMPROVING OUTPUT OF A MODEL - Example methods, apparatuses, or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate or otherwise support one or more processes or operations for a Jabba-type override for correcting or improving output of a model, such as a machine-learned model, for example. | 2014-09-18 |
20140279744 | CONTINUOUS INTERACTION LEARNING AND DETECTION IN REAL-TIME - Systems and methods may provide for partitioning a plurality of training samples into a first sequential list of centroids, removing one or more repeating centroids in the first sequential list of centroids to obtain a first reduced list of centroids and generating a set of Hidden Markov Model (HMM) parameters based on the first reduced list of centroids. Additionally, a plurality of detection samples may be partitioned into a second sequential list of centroids, wherein one or more repeating centroids in the second sequential list of centroids may be removed to obtain a second reduced list of centroids. The second reduced list of centroids may be used to determine a match probability for the plurality of detection samples against the set of HMM parameters. In one example, the reduced lists of centroids lack temporal variability. | 2014-09-18 |
20140279745 | CLASSIFICATION BASED ON PREDICTION OF ACCURACY OF MULTIPLE DATA MODELS - A dynamic classifier for performing binary classification of instance data using oracles that predict accuracy of predictions made by corresponding models. An oracle corresponding to a model is trained to generate a confidence value that represents accuracy of a prediction made by the model. Based on the confidence value and predictions, one of multiple models is selected and its prediction is used as an intermediate prediction. The intermediate prediction may be used in conjunction with another prediction generated using a different algorithm to generate a final prediction. By using the confidence value for each model, a more accurate prediction can be made. | 2014-09-18 |
20140279746 | EXPERT SYSTEM FOR DETERMINING PATIENT TREATMENT RESPONSE - A medical digital expert system to predict a patient's response to a variety of treatments (using pre-treatment information) is described. The system utilizes data fusion, advanced signal/information processing and machine learning/inference methodologies and technologies to integrate and explore diverse sets of attributes, parameters and information that are available to select the optimal treatment choice for an individual or for a subset of individuals suffering from any illness or disease including psychiatric, mental or neurological disorders and illnesses. The methodology and system can also be used to determine or confirm medical diagnosis, estimate the level, index, severity or critical medical parameters of the illness or condition, or provide a list of likely diagnoses for an individual suffering/experiencing any illness, disorder or condition. | 2014-09-18 |
20140279747 | System and Method for Model-based Inventory Management of a Communications System - A method for management entity operations includes receiving a request to collect data for an entity in a communications system, collecting the data for the entity utilizing a set of protocols selected using knowledge defined by a first data model of a data model list derived from an information model of the communications system, and saving the data collected. | 2014-09-18 |
20140279748 | METHOD AND PROGRAM STRUCTURE FOR MACHINE LEARNING - A method using a recognizer program structure is used in a program that is learned over training data. The method includes (a) for each vector in an input tuple of vectors, (i) mapping the vector to one of a domain index; (ii) using the domain index to select one or more corresponding linear transformations; (iii) applying one or more of the selected linear transformations on the vector to obtain a resulting vector in a first intermediate space; and (iv) applying a predetermined function on each element of the resulting vector to obtain an output vector in a second intermediate space; and (b) mapping the resulting vectors of the second intermediate space by linear transformation to obtain an output tuple of vectors in R | 2014-09-18 |
20140279749 | MECHANISM FOR FACILITATING IMPROVED SEARCHING - Improved integrated search techniques. A request for performance of a search for objects is received within a multi-tenant database environment having a plurality of tenants each having individual tenant information. A query is generated in response to the request. The query is specialized based on tenant information corresponding to a tenant from which the request originates. The tenant information is retrieved from the multi-tenant database environment. The query is performed on information stored in the multi-tenant database environment. Results of the query are presented to a user in a graphical user interface. | 2014-09-18 |
20140279750 | METHOD AND SYSTEM FOR IDENTIFYING A CLEAN ENDPOINT TIME FOR A CHAMBER - Systems and methods are provided for determining a clean endpoint time for a current run of a chamber. The clean endpoint time for the current run may be determined by determining that a chamber parameter, such as a chamber pressure, has stabilized. Historical clean endpoint time data is updated by adding the clean endpoint time for the current run of the chamber. A recommended clean endpoint time is then determined for the chamber based on the updated historical clean endpoint time data. | 2014-09-18 |
20140279751 | AGGREGATION AND ANALYSIS OF MEDIA CONTENT INFORMATION - Disclosed are the method and apparatus for collecting and analyzing media content metadata. The technology retrieves web documents referencing media objects from web servers. Metadata of the media objects such as global tags and category weight values are generated from the web documents. Affinity values between user identities and the media objects are generated based on online behaviors of the users interacting with the media objects. Based on the affinity values and metadata of the media objects, the technology can provide recommendations of media objects. | 2014-09-18 |
20140279752 | System and Method for Generating Ultimate Reason Codes for Computer Models - A system and method for generating ultimate reason codes for computer models is provided. The system for generating ultimate reason codes for computer models comprising a computer system for receiving a data set, and an ultimate reason code generation engine stored on the computer system which, when executed by the computer system, causes the computer system to train a base model with a plurality of reason codes, wherein each reason code includes one or more variables, each of which belongs to only one reason code, train a subsequent model using a subset of the plurality of reason codes, determine whether a high score exists in the base model, determine a scored difference if a high score exists in the base model, and designate a reason code having a largest drop of score as an ultimate reason code. | 2014-09-18 |
20140279753 | METHODS AND SYSTEM FOR PROVIDING SIMULTANEOUS MULTI-TASK ENSEMBLE LEARNING - A complete end-to-end modeling system is provided that includes data sampling, feature engineering, action labeling, and model learning or learning from models built based on collected data. The end-to-end modeling process is performed via an automatic mechanism with minimal or reduced human intervention. A processor-readable medium is disclosed, storing processor-executable instructions to instantiate an automated data sampling and prediction structure training component, the automated data sampling and prediction structure training component being configured to automatically collect user event data samples, and use the collected user event data samples to train multiple prediction structures in parallel. | 2014-09-18 |
20140279754 | SELF-EVOLVING PREDICTIVE MODEL - Systems and methods are provided for predicting clinical parameters. A model of a plurality of models having a sufficient accuracy, given a received set of predictors, is selected. A value for a clinical parameter is predicted from the selected model and the set of predictors to provide a predicted value. A value for the clinical parameter is measured, and the model is updated according to the set of predictors and the measured value. | 2014-09-18 |
20140279755 | MANIFOLD-AWARE RANKING KERNEL FOR INFORMATION RETRIEVAL - A manifold-aware ranking kernel (MARK) for information retrieval is described herein. The MARK is implemented by using supervised and unsupervised learning. MARK is ranking-oriented such that the relative comparison formulation directly targets on the ranking problem, making the approach optimal for information retrieval. MARK is also manifold-aware such that the algorithm is able to exploit information from ample unlabeled data, which helps to improve generalization performance, particularly when there are limited number of labeled constraints. MARK is nonlinear: as a kernel-based approach, the algorithm is able to lead to a highly non-linear metric which is able to model complicated data distribution. | 2014-09-18 |
20140279756 | CROSS MEDIA RECOMMENDATION - Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain. | 2014-09-18 |
20140279757 | APPARATUS, SYSTEMS, AND METHODS FOR GROUPING DATA RECORDS - The present application relates to apparatus, systems, and methods for grouping data records based on entities referenced by the data records. The disclosed grouping mechanism can include determining a pair-wise similarity between a large number of data records, and clustering a subset of the data records based on their pair-wise similarity. | 2014-09-18 |
20140279758 | COMPUTATIONAL METHOD FOR PREDICTING FUNCTIONAL SITES OF BIOLOGICAL MOLECULES - In a general aspect, a method for inferring one or more biomolecule-to-biomolecule interaction sites includes receiving data representative of a plurality of prediction models. Each prediction model is associated with a different atom type of a plurality of atom types and characterizes biomolecule-to-biomolecule interaction site specific patterns common to a plurality of three dimensional probability density maps. Each three dimensional probability density map is associated with a corresponding biomolecule of a plurality of biomolecules included in a training data set and represents a probability of a non-covalent interacting atom on a surface of the corresponding biomolecule interacting with the atom type associated with the prediction model. Data representative of a query biomolecule is received, the data including one or more unknown biomolecule-to-biomolecule interaction sites. The one or more unknown biomolecule-to-biomolecule interaction sites of the query biomolecule are inferred based on the data representative of the plurality of prediction models. | 2014-09-18 |
20140279759 | TRAINING OF STORAGE DEVICES IN COMPUTING SYSTEMS AND ENVIRONMENTS - Storage devices and components, including memory components (e.g., non-volatile memory) can be trained by executable code that facilitates and/or performs reads and/or write requests to one or more storage sub-modules of a storage component (e.g., memory configured on a memory channel) made up of multiple storage components (e.g., DIMMs). The executable code can also train multiple storage components at the same time and/or in parallel. | 2014-09-18 |
20140279760 | Data Analysis Computer System and Method For Conversion Of Predictive Models To Equivalent Ones - The present invention addresses two ubiquitous and pressing problems of modern data analytics technology. Many modern pattern recognition technologies produce models with excellent predictivity but (a) they are “black boxes”, that is they are opaque to the user; (b) they are too large, and/or expensive to execute in less powerful computing platforms. The invention “opens up” a black box model by converting it to a compact and understandable model that is functionally equivalent. The invention also converts a predictive model into a functionally equivalent model into a form that can be implemented and deployed more easily or efficiently in practice. The benefits include: model understandability and defensibility of modeling. A particularly interesting application is that of understanding the decision making of humans, comparison of the behavior of a human or computerized decision process against another and use to enhance education and guideline compliance/adherence detection and improvement. The invention can be applied to practically any field where predictive modeling (classification and regression) is desired because it relies on extremely broad distributional assumptions that are valid in numerous fields. | 2014-09-18 |
20140279761 | Document Coding Computer System and Method With Integrated Quality Assurance - The present invention consists of a computer-implemented system and method for automatically analyzing and coding documents into content categories suitable for high cost, high yield settings where quality and efficiency of classification are essential. A prototypical example application field is legal document predictive coding for purposes of e-discovery and litigation (or litigation readiness) where the automated classification of documents as “responsive” or not must be (a) efficient, (b) accurate, and (c) defensible in court. Many text classification technologies exist but they focus on the relatively simple steps of using a training method on training data, producing a model and testing it on test data. They invariably do not address effectively and simultaneously key quality assurance requirements. The invention applies several data design and validation steps that ensure quality and removal of all possible sources of document classification error or deficiencies. The invention employs multiple classification methods, preprocessing methods, visualization and organization of results, and explanation of models which further enhance predictive quality, but also ease of use of models and user acceptance. The invention can be applied to practically any field where text classification is desired. | 2014-09-18 |
20140279762 | ANALYTICAL NEURAL NETWORK INTELLIGENT INTERFACE MACHINE LEARNING METHOD AND SYSTEM - A learning framework and methods of machine learning are disclosed. Specifically, an Analytical Neural Network Intelligent Interface (ANNII) is disclosed that includes the ability to analyze incoming data in substantially real-time and determine whether or not the data is statistically anomalous data. Learning models can then be updated depending upon whether or not the data is determined to be statistically anomalous data or not. | 2014-09-18 |
20140279763 | System and Method for Automated Scoring of a Summary-Writing Task - In accordance with the teachings described herein, systems and methods are provided for measuring a user's comprehension of subject matter of a text. A summary generated by the user is received, where the summary summarizes the text. The summary is processed to determine a first numerical measure indicative of a similarity between the summary and a reference summary. The summary is processed to determine a second numerical measure indicative of a degree to which a single sentence of the summary summarizes an entirety of the text. The summary is processed to determine a third numerical measure indicative of a degree of copying in the summary of multi-word sequences present in the text. A numerical model is applied to the first numerical measure, the second numerical measure and the third numerical measure to determine a score for the summary indicative of the user's comprehension of the subject matter of the text. | 2014-09-18 |
20140279764 | GENERATING EVENT DEFINITIONS BASED ON SPATIAL AND RELATIONAL RELATIONSHIPS - Data from one or more sensors is input to a workflow and fragmented to produce HyperFragments. The HyperFragments of input data are processed by a plurality of Distributed Experts, who make decisions about what is included in the HyperFragments or add details relating to elements included therein, producing tagged HyperFragments, which are maintained as tuples in a Semantic Database. Algorithms are applied to process the HyperFragments to create an event definition corresponding to a specific activity. Based on related activity included in historical data and on ground truth data, the event definition is refined to produce a more accurate event definition. The resulting refined event definition can then be used with the current input data to more accurately detect when the specific activity is being carried out. | 2014-09-18 |
20140279765 | EARLY GENERATION OF INDIVIDUALS TO ACCELERATE GENETIC ALGORITHMS - While at least one candidate solution of a first generation of candidate solutions remains to be evaluated in accordance with a fitness function for an optimization problem, a plurality of candidate solutions is selected from the first generation of candidate solutions to participate in a tournament. It is determined whether each of the plurality of candidate solutions selected to participate in the tournament have been evaluated in accordance with the fitness function. If all have been evaluated, then one or more winners of the tournament are selected from the plurality of candidate solutions of the first generation of candidate solutions. A candidate solution of a second generation of candidate solutions is created with the selected one or more winners of the tournament in accordance with a genetic operator. | 2014-09-18 |
20140279766 | SYSTEMS AND METHODS FOR VECTOR SCALABILITY OF EVOLUTIONARY ALGORITHMS - Systems and methods are provided to enable vector scalability in evolutionary algorithms to enable execution of optimization problems having a relatively large number of variables. A subset of the total number of variables of a chromosome data structure may be considered relative to a baseline known solution for the purpose of evaluating one or more objective functions of the evolutionary algorithm. | 2014-09-18 |
20140279767 | DETERMINING A THREAT LEVEL FOR ONE OR MORE INDIVIDUALS - A system and computer-implemented method for determining a threat level for one or more individuals includes accessing a data structure to obtain aggregated data stored therein, wherein the aggregated data comprises at least one of communication history data or transaction history data for one or more individuals. One or more predetermined metrics are applied to the obtained aggregated data, to determine threat level information for the one or more individuals. The determined threat level information is provided for display. | 2014-09-18 |
20140279768 | DEVICE AND RELATED METHOD FOR SCORING APPLICATIONS RUNNING ON A NETWORK - A function is provided for effectively identifying computer applications running on a network. The function receives information related to frames of packets moving through the network. The information is compared to known information about computer applications. The known information is obtained from a plurality of mechanisms, including the option of obtaining it through custom mechanisms. The comparison information is scored for each of the plurality of mechanisms and those scores are combined to establish a single score indicative of the likely computer application associated with the received frames. One or more mathematical operations can be used to combine the scores. The mechanisms may be weighted for likely accuracy and the score that is established may include with it an indication of the level of confidence in that score. One or more of the plurality of mechanisms may be used to weight others of the types of mechanisms. | 2014-09-18 |
20140279769 | PROCESS MODEL GENERATED USING BIASED PROCESS MINING - Embodiments relate to a method, system, and computer program product for a process model. The method includes extracting data associated with a process execution trace of a running process and extracting any prior knowledge data relating to the running process. The method also includes calculating at least one transition confidence parameter for the prior knowledge data; and identifying any existing process models relating to the running process. A confidence trace bias is also generated for any existing process model identified. An enhanced bias value is then calculated by combining the confidence trace bias value and value of the transition confidence parameter. Using as input the extracted process execution trace data, the prior knowledge data, the identified existing model and the enhanced bias value, a learned process model is then generated. | 2014-09-18 |
20140279770 | ARTIFICIAL NEURAL NETWORK INTERFACE AND METHODS OF TRAINING THE SAME FOR VARIOUS USE CASES - An Artificial Neural Network Interface (ANNI) is disclosed along with use cases for the same. The ANNI utilizes one or more decision trees and/or probabilistic/combinatoric analysis to determine optimal responses to current conditions. The ANNI is also enabled to learn new conditions that are accepted as normal and, in response thereto, update the decision tree(s). | 2014-09-18 |
20140279771 | Novel Quadratic Regularization For Neural Network With Skip-Layer Connections - According to one aspect of the invention, target data comprising observations is received. A neural network comprising input neurons, output neurons, hidden neurons, skip-layer connections, and non-skip-layer connections is used to analyze the target data based on an overall objective function that comprises a linear regression part, the neural network's unregularized objective function, and a regularization term. An overall optimized first vector value of a first vector and an overall optimized second vector value of a second vector are determined based on the target data and the overall objective function. The first vector comprises skip-layer weights for the skip-layer connections and output neuron biases, whereas the second vector comprises non-skip-layer weights for the non-skip-layer connections. | 2014-09-18 |
20140279772 | NEURONAL NETWORKS FOR CONTROLLING DOWNHOLE PROCESSES - An apparatus for processing signals downhole includes a carrier configured to be conveyed through a borehole penetrating an earth formation and a container disposed at the carrier and configured to carry biological material. A cultured biological neural network is disposed at the container, the neural network being capable of processing a network input signal and providing a processed network output signal. One or more electrodes are in electrical communication with the neural network, the one or more electrodes being configured to communicate the network input signal into the neural network and to communicate the network output signal out of the neural network. | 2014-09-18 |
20140279773 | Scoring Concept Terms Using a Deep Network - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scoring concept terms using a deep network. One of the methods includes receiving an input comprising a plurality of features of a resource, wherein each feature is a value of a respective attribute of the resource; processing each of the features using a respective embedding function to generate one or more numeric values; processing the numeric values to generate an alternative representation of the features of the resource, wherein processing the floating point values comprises applying one or more non-linear transformations to the floating point values; and processing the alternative representation of the input to generate a respective relevance score for each concept term in a pre-determined set of concept terms, wherein each of the respective relevance scores measures a predicted relevance of the corresponding concept term to the resource. | 2014-09-18 |
20140279774 | Classifying Resources Using a Deep Network - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scoring concept terms using a deep network. One of the methods includes receiving an input comprising a plurality of features of a resource, wherein each feature is a value of a respective attribute of the resource; processing each of the features using a respective embedding function to generate one or more numeric values; processing the numeric values using one or more neural network layers to generate an alternative representation of the features, wherein processing the floating point values comprises applying one or more non-linear transformations to the floating point values; and processing the alternative representation of the input using a classifier to generate a respective category score for each category in a pre-determined set of categories, wherein each of the respective category scores measure a predicted likelihood that the resource belongs to the corresponding category. | 2014-09-18 |
20140279775 | DECISION TREE INSIGHT DISCOVERY - Techniques for presenting insight into classification trees may include performing a grouping analysis to group leaf nodes of a classification tree into a significant group and an insignificant group, performing influential target category analysis to identify one or more influential target categories for the leaf nodes of the classification tree in the significant group, and presenting one or more insights into the classification tree based on the grouping analysis and the influential target category analysis. Techniques for presenting insight into regression trees may include performing a grouping analysis to group leaf nodes of a regression tree into a high group and a low group, performing unusual node detection analysis to detect one or more outlier nodes in the high group and in the low group, and presenting one or more insights into the regression tree based on the grouping analysis and the unusual node detection analysis | 2014-09-18 |
20140279776 | METHODS AND APPARATUSES FOR PROVIDING DATA RECEIVED BY A STATE MACHINE ENGINE - An apparatus can include a first state machine engine configured to receive a first portion of a data stream from a processor and a second state machine engine configured to receive a second portion of the data stream from the processor. The apparatus includes a buffer interface configured to enable data transfer between the first and second state machine engines. The buffer interface includes an interface data bus coupled to the first and second state machine engines. The buffer interface is configured to provide data between the first and second state machine engines. | 2014-09-18 |
20140279777 | SIGNAL PROCESSING SYSTEMS - We describe a signal processor, the signal processor comprising: a probability vector generation system, wherein said probability vector generation system has an input to receive a category vector for a category of output example and an output to provide a probability vector for said category of output example, wherein said output example comprises a set of data points, and wherein said probability vector defines a probability of each of said set of data points for said category of output example; a memory storing a plurality of said category vectors, one for each of a plurality of said categories of output example; and a stochastic selector to select a said stored category of output example for presentation of the corresponding category vector to said probability vector generation system; wherein said signal processor is configured to output data for an output example corresponding to said selected stored category. | 2014-09-18 |
20140279778 | Systems and Methods for Time Encoding and Decoding Machines - Systems and methods for system identification, encoding and decoding signals in a non-linear system are disclosed. An exemplary method can include receiving the one or more input signals and performing dendritic processing on the input signals. The method can also encode the output of the dendritic processing of the input signals, at a neuron, to provide encoded signals. | 2014-09-18 |
20140279779 | SYSTEM AND METHOD FOR DETECTING PLATFORM ANOMALIES THROUGH NEURAL NETWORKS - A system and method for detecting behavior of a computing platform that includes obtaining platform data; for each data motif identifiers in a set data motif identifiers, performing data motif detection on data in an associated timescale, wherein a first data motif identifier operates on data in a first timescale, wherein a second data motif identifier operates on data in a second timescale, wherein the first timescale and second timescale are different; in a neural network model, synthesizing platform data anomaly detection with at least a set of features inputs from data motif detection of the set of motif identifiers; and signaling if a platform data anomaly is detected through the neural network model. | 2014-09-18 |
20140279780 | METHOD AND SYSTEM FOR RECOMMENDING CROWDSOURCING PLATFORMS - A method and system for recommending one or more crowdsourcing platforms from a plurality of crowdsourcing platforms to a requester is disclosed. The method includes receiving values corresponding to one or more parameters of one or more tasks from the requester. In response to the received values recommending the one or more crowdsourcing platforms to the requester based on the values and one or more statistical models maintained for the one or more crowdsourcing platforms, wherein the one or more statistical models corresponds to mathematical models representing performances of the one or more crowdsourcing platforms over a period of time. | 2014-09-18 |
20140279781 | METHOD AND SYSTEM FOR RECORDING RECOMMENDED CONTENT USING CLUSTERING - A method and system for storing push content includes a user device having a memory and a viewer tracking module generating a viewed content history for content corresponding to viewed content at the user device. A recommendation recording module compares the viewed content history and push content and stores at least one push content at the user device in response comparing to form a recorded content push list. A display displays the recorded content push list corresponding to the content stored in the user device. | 2014-09-18 |
20140279782 | SOCIAL NETWORK-INFLUENCED INTEREST DETECTION - Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting users that are connected to a particular user; accessing, for each of the selected users, an interest score of the selected user that reflects the selected user's predicted interest in the particular topic, or interest data that that is used to determine the interest score of the selected user; accessing a model that is used for generating the interest score of the particular user that reflects the particular user's predicted interest in the particular topic, wherein the interest score of the particular user is generated based at least on the interest scores or interest data of the selected users for the particular topic; and applying the interest scores or interest data of the selected users for the particular topic to the model to generate the interest score of the particular user for the particular topic. | 2014-09-18 |
20140279783 | EVALUATION OF PREDICTIONS IN THE ABSENCE OF A KNOWN GROUND TRUTH - Disclosed is a novel system, and method to evaluate a prediction of a possibly unknown outcome out of a plurality of predictions of that outcome. The method begins with accessing a particular prediction of an outcome out of a plurality of predictions of that outcome in which the outcome may be unknown. Next, a subsample of the plurality of predictions of the outcome is accessed. The subsample can possibly include the particular prediction. A consensus prediction of the outcome based on the subsample of the plurality of predictions is determined. A proximity of the particular prediction to the consensus prediction is determined. Each prediction is ranked out of the plurality of predictions in an order of a closest in proximity to the consensus prediction to a farthest in proximity to the consensus prediction. | 2014-09-18 |
20140279784 | PARTIAL PREDICTIVE MODELING - A computerized method disclosed herein for analyzing data based on multiple disparate datasets generates a unified predictive model based on a unified dataset, wherein the unified dataset includes data from the multiple disparate datasets. The unified predictive model is partitioned into a number of partial predictive models. A number partial predictions are generated by applying each of the partial predictive models to data from each of the plurality of datasets and the plurality of partial predictions are combined to generate a unified prediction. | 2014-09-18 |
20140279785 | METHODS, SYSTEMS, AND APPARATUS FOR PREDICTING CHARACTERISTICS OF A USER - Methods, systems, and apparatus for predicting the characteristics of a user are described. A model based on a conditional multivariate normal distribution and social relationship information between the selected user and each of one or more other users are obtained. One or more characteristics of the selected user are determined based on the model and the social relationship information. The user characteristics may be determined by adjusting the characteristics of a typical source user according to the model and the social relationship information of the selected user. | 2014-09-18 |
20140279786 | APPLICATION-CONTROLLED GRANULARITY FOR POWER-EFFICIENT CLASSIFICATION - Systems and methods for providing application-controlled, power-efficient context (state) classification are described herein. An apparatus for performing context classification with adjustable granularity as described herein includes a classifier controller configured to receive a request for a context classification and a granularity input associated with the request; and a context classifier communicatively coupled to the classifier controller and configured to receive the request and the granularity input from the classifier controller, to select a resource usage level for the context classification based on the granularity input, wherein a granularity input indicating a higher granularity level is associated with a higher resource usage level and a granularity input indicating a lower granularity level is associated with a lower resource usage level, and to perform the context classification at the selected resource usage level. | 2014-09-18 |
20140279787 | Systems And Methods for an Adaptive Application Recommender - With the growing number of downloaded applications on devices, especially on ones with limited screen real estate, users need a quick and pain-free way to locate applications. In accordance with one or more embodiments of the present invention, a system and methods are provided for generating an application selection recommendation. | 2014-09-18 |
20140279788 | Predictive System for Designing Enterprise Applications - Predictive systems for designing enterprise applications include memory structures that output predictions to a user. The predictive system may include an HTM structure that comprises a tree-shaped hierarchy of memory nodes, wherein each memory node has a learning and memory function, and is hierarchical in space and time that allows them to efficiently model the structure of the world. The memory nodes learn causes, predicts with probability values, and form beliefs based on the input data, where the learning algorithm stores likely sequence of patterns in the nodes. By combining memory of likely sequences with current input data, the nodes may predict the next event. The predictive system may employ an HHMM structure comprising states, wherein each state is itself an HHMM. The states of the HHMM generate sequences of observation symbols for making predictions. | 2014-09-18 |
20140279789 | PREDICTING AN IDENTITY OF A PERSON BASED ON AN ACTIVITY HISTORY - Systems and methods for predicting an identity of a person are provided. In some aspects, a list of subject activities accessed by a subject person is received. For each of a plurality of stored persons, a stored list of activities accessed with by the stored person is accessed in one or more data repositories. An intersection is calculated between the list of subject activities and the stored list of activities for at least one stored person from the plurality of stored persons. That the subject person is likely to correspond to the at least one stored person from among the plurality of stored persons is predicted, based on the calculated intersection. An indication that the subject person is likely to correspond to the at least one stored person from among the plurality of stored persons is provided. | 2014-09-18 |
20140279790 | CONTEXT AWARE LOCALIZATION, MAPPING, AND TRACKING - Exemplary methods, apparatuses, and systems infer a context of a user or device. A computer vision parameter is configured according to the inferred context. Performing a computer vision task, in accordance with the configured computer vision parameter. The computer vision task may by at least one of: a visual mapping of an environment of the device, a visual localization of the device or an object within the environment of the device, or a visual tracking of the device within the environment of the device. | 2014-09-18 |
20140279791 | EVALUATION OF PREDICTIONS IN THE ABSENCE OF A KNOWN GROUND TRUTH - Disclosed is a novel system, and method to evaluate a prediction of a possibly unknown outcome out of a plurality of predictions of that outcome. The method begins with accessing a particular prediction of an outcome out of a plurality of predictions of that outcome in which the outcome may be unknown. Next, a subsample of the plurality of predictions of the outcome is accessed. The subsample can possibly include the particular prediction. A consensus prediction of the outcome based on the subsample of the plurality of predictions is determined. A proximity of the particular prediction to the consensus prediction is determined. Each prediction is ranked out of the plurality of predictions in an order of a closest in proximity to the consensus prediction to a farthest in proximity to the consensus prediction. | 2014-09-18 |
20140279792 | METHOD AND SYSTEM FOR MAKING CUSTOMIZED FORMULATIONS FOR INDIVIDUALS - The one or more embodiments disclosed herein provide a method for automatically assembling multiple compounds into a single edible custom composition, in which each compound is individually customized to proportions formulated from a profile of an individual or group. The single custom mixture can contain a plurality of compounds including foods or flavors, nutritional additives, herbals, biologics, or pharmacologically active substances. Using the method and a related algorithm, the formulation of a custom mixture is suggested. | 2014-09-18 |
20140279793 | SYSTEMS AND METHODS FOR PROVIDING RELEVANT PATHWAYS THROUGH LINKED INFORMATION - Systems and methods for predicting and monetizing information pathways. An indication is received that a user has visited a webpage and, based on information associated with the visit, a predictive model is used to predict a plurality of webpages that are likely to be visited by the user. The user is then provided with a subset of the predicted webpages as a traversable pathway of webpages. Information relating to the user's traversal of the pathway can be collected and used to facilitate the provision of an advertisement to the user. | 2014-09-18 |
20140279794 | Data Analysis Computer System and Method for Organizing, Presenting, and Optimizing Predictive Modeling - Predictive modeling is an important class of data analytics with applications in numerous fields. Once a predictive model is built, validated, and applied on a set of objects, by a data analytics system (or even by manual modeling), consumers of the model information need assistance to navigate through the results. This is because both regression and classification models that output continuous values (eg, probability of belonging to a class) are often used to rank objects and then a thresholding of the ranked scores needs to be used to separate objects into a “positive” and a “negative” class. The choice of threshold greatly affects the true positive, false positive, true negative, and false negative results of the model's application. An ideal data analytics system should allow the user to understand the tradeoffs of different threshold values for different thresholds. The user interface should convey this information in an intuitive manner and provide the ability to vary the threshold interactively while simultaneously presenting the effects of thresholding on predictivity. This is precisely the function of the present invention. In addition to manual thresholding, the invention also allows for the thresholding to be performed by fully automated means (via standard statistical optimization methods) once a user has identified the desired balance of false positives and false negatives (or other predictivity metrics of interest). The invention can be applied to any application field of predictive modeling. | 2014-09-18 |
20140279795 | Facility State Monitoring Method and Device for Same - In case-based anomaly indication detection in a facility, there are problems such as error generation due to insufficient learning data or execution difficulty due to increased memory capacity and calculation time when the learning data period has been increased to obtain the learning data sufficiently. Provided is a method for monitoring facility state on the basis of a time series signal outputted from the facility, wherein an operation pattern label for each fixed interval is assigned on the basis of the time series signal, learning data is selected on the basis of the operation pattern label for each fixed interval, a normal model is created on the basis of the selected learning data, an anomaly measure is calculated on the basis of the time series signal and the normal model, and the facility state is determined to be anomaly or normal on the basis of the calculated anomaly measure. | 2014-09-18 |
20140279796 | PROGRAMMABLE DEVICE, HIERARCHICAL PARALLEL MACHINES, AND METHODS FOR PROVIDING STATE INFORMATION - Programmable devices, hierarchical parallel machines and methods for providing state information are described. In one such programmable device, programmable elements are provided. The programmable elements are configured to implement one or more finite state machines. The programmable elements are configured to receive an N-digit input and provide a M-digit output as a function of the N-digit input. The M-digit output includes state information from less than all of the programmable elements. Other programmable devices, hierarchical parallel machines and methods are also disclosed. | 2014-09-18 |
20140279797 | BEHAVIORAL RULES DISCOVERY FOR INTELLIGENT COMPUTING ENVIRONMENT ADMINISTRATION - A management system for determining causal relationships among system entities may include a causal relationship detector configured to receive events from a computing environment having a plurality of entities, and detect causal relationships among the plurality of entities, during runtime of the computing environment, based on the events, and a rules converter configured to convert one or more of the causal relationships into at least one behavioral rule. The at least one behavioral rule may indicate a causal relationship between at least two entities of the plurality of entities. | 2014-09-18 |
20140279798 | DERIVATION AND PRESENTATION OF EXPERTISE SUMMARIES AND INTERESTS FOR USERS - Architecture that automatically generate concise descriptions of users in social media. The descriptions communicate classification or category of a given social media user in a small amount of viewing space. The description can be based on available metadata (e.g., user profile biography) and/or other information about that person, as may be obtained from the information data sources (e.g., structured knowledge bases) on networks such as the Internet and enterprises, for example. The descriptions can also be query-dependent, by assuming there is some relationship between the social media user and a query, in which case, the descriptions illustrate that relationship. | 2014-09-18 |
20140279799 | PROVIDING REWARDS BUCKETS AND SAVINGS TOWARDS SPECIFIC GOALS - Embodiments of the invention relate to systems, methods, and computer program products for providing a rewards program. The system, method, and computer program product are configured to determine that a customer has completed an action; determine that the customer has earned a reward based on the action; determine a category associated with the reward; and apply the reward to the category. In some situations, the categories are default categories provided by the financial institution. In other situations, the categories are defined by the customer. The system determines which category an earned award is routed into using a decision engine that evaluates the award and/or the action completed by the customer and compares the award and/or action to rules, such as default rules, custom rules, or dynamic rules. The categories may also include goals and the system assists in tracking customer's progress towards the goal. | 2014-09-18 |
20140279800 | Systems and Methods for Artificial Intelligence Decision Making in a Virtual Environment - Disclosed is a AI decision making solution under which the actions, reactions and behavior of an AI entity are defined in a virtual environment. In addition to gathering user interactive data within a given scenario, the disclosed principles also provide for a periodic analysis of the entire virtual environment, regardless of user interaction. This allows the disclosed AI entity to make more accurate decisions by constantly taking into account the status of the environment in addition to user interactions with the environment or other characters. Also, the disclosed principles provide an AI solution capable of modifying not only the weights assignable to data used in the decision making process, but also modifying the actual rules of the decision making process itself depending on the gathered and analyzed weighted data. As a result, the disclosed AI entity is capable of making varying decisions on the same or similar collection of data. | 2014-09-18 |
20140279801 | INTERACTIVE METHOD TO REDUCE THE AMOUNT OF TRADEOFF INFORMATION REQUIRED FROM DECISION MAKERS IN MULTI-ATTRIBUTE DECISION MAKING UNDER UNCERTAINTY - There is provided a method, a system and a computer program product for supporting a decision making process. The system receives a decision model from a decision maker, the decision model used for determining a solution to a decision problem based on attributes and uncertainties of the decision problem. The decision problem includes information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem. The system determines whether the received decision model can be solved without receiving any preference information from the decision maker. The system receives partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information. The system solves the decision model with the partially specified preference information. The system recommends, based on the solution, one or more decisions to the decision maker. | 2014-09-18 |
20140279802 | METHODS AND SYSTEMS FOR PROPAGATING INFORMATION IN COLLABORATIVE DECISION-MAKING - A computer includes a processor and a memory device. The computer is configured to a) receive decision-making criteria from at least one of at least a portion of a plurality of agents associated with a plurality of agent devices, the memory device, and a user, b) generate valid decision combinations using at least a portion of received decision-making criteria, c) transmit, to the plurality of agents, valid decision combinations, d) receive, from a deciding agent, a decision, and e) constrain, using the received decision, valid decision combinations. The computer is configured to f) return to c) until determining that no more decisions can be received. The computer is configured to g) transmit a final decision set to the plurality of agents upon determining that no more decisions can be received. The final decision set represents a complete combination of decisions including at least a portion of received decisions. | 2014-09-18 |
20140279803 | DISAMBIGUATING DATA USING CONTEXTUAL AND HISTORICAL INFORMATION - Techniques for disambiguating data using contextual and historical information include determining that data is potentially associated with two or more classifications of a plurality of classifications; obtaining contextual information associated with the data; obtaining historical information associated with a user of the computing system; and determining that the data is more likely associated with one classification of the two or more classifications than other classifications of the two or more classifications based on the contextual information and the historical information. | 2014-09-18 |
20140279804 | JABBA-TYPE CONTEXTUAL TAGGER - Example methods, apparatuses, or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate or otherwise support one or more processes or operations for a Jabba-type contextual tagger. | 2014-09-18 |