Balasubramanyan
Arun Balasubramanyan, Chennai IN
Patent application number | Description | Published |
---|---|---|
20140130180 | CONTROL OF ACCESS TO FILES - A method, system and program product for using access-control lists to control access to categorized computer files. Two or more computer files are each associated with one of a set of possible classifications that fall within a single category and an access-control list associates a user with a subset of these classifications. In response to the user's request for access to one of these files, where the request specifies the requested file but does not specify the category of the requested file, the processor identifies the requested file's category based on that file's associated classifications, checks the access-control list to determine that the user is authorized to access files of the identified category, and then grants the requesting user access to the requested file. | 05-08-2014 |
20140351708 | CUSTOMIZING A DASHBOARD RESPONSIVE TO USAGE ACTIVITY - Embodiments of the present invention disclose a method, computer program product, and system for user interface customization. A computer records activity of a first computer on a user interface. The computer determines one or more repetitive activities of the first computer utilizing the recorded activity of the first computer. The computer determines a customized user interface for the first computer corresponding to the one or more repetitive activities of the first computer. In another embodiment, the computer initiates display of the customized user interface to the first computer. In another embodiment, the recorded activity of the first computer includes navigation through links in the user interface, applying filters to data in the user interface, and accessing data on the user interface. | 11-27-2014 |
Arun Balasubramanyan, Velacherry IN
Patent application number | Description | Published |
---|---|---|
20150339358 | MANAGING QUERIES IN BUSINESS INTELLIGENCE PLATFORMS - A method is provided for managing queries in business intelligence platforms. The method includes receiving, by a processor, a first query requesting data from at least one business intelligence content, the first query having a first format. The method further includes determining, by the processor, at least one requirement to complete the first query. The method further includes converting, by the processor, the first query to a second query configured to be used by an Extract, Transform, and Load (ETL) program, in response to determining that the at least one requirement exceeds a threshold, the second query having a second format. | 11-26-2015 |
Ramnath Balasubramanyan, Mountain View, CA US
Patent application number | Description | Published |
---|---|---|
20080243905 | Attribute extraction using limited training data - Techniques are described for reducing the false positive rate of regular expression attribute extractions via a specific data representation and a machine learning method that can be trained at a much lower cost (much fewer labeled examples) than would be required by a full scale machine learning solution. Attribute determinations made using the regular expression technique are represented as skeleton tokens. The skeleton tokens, along with accurate attribute determinations, are provided to a machine-learning mechanism to train the machine-learning mechanism. Once trained, the machine-learning mechanism is used to predict the accuracy of attribute determinations represented by skeleton tokens generated for not-yet-analyzed input text. | 10-02-2008 |
20110137908 | ASSIGNING INTO ONE SET OF CATEGORIES INFORMATION THAT HAS BEEN ASSIGNED TO OTHER SETS OF CATEGORIES - Techniques are described for assigning, to target categories of a target scheme, items that have been obtained from a plurality of sources. In situations in which one or more of the sources has organized its information according to a source scheme that differs from the target scheme, the assignment may be based, in part, on an estimate of the probability that items from a particular source category should be assigned to a particular target category. Such probability estimates may be based on how many training set items associated with the particular source category have been assigned to the particular target category. Source categories may be grouped into clusters. The probability estimates may also be based on how many training set items within the cluster to which the particular source category has been mapped, have been assigned the particular target category. | 06-09-2011 |