Patent application number | Description | Published |
20090055380 | Predictive Stemming for Web Search with Statistical Machine Translation Models - Techniques for determining when and how to transform words in a query to return the most relevant search results while minimizing computational overhead are provided. A dictionary is generated based upon words used in a specified number of previous most frequent search queries and comprises lists of transformations that may include variants based upon the stems of words, synonyms, and abbreviation expansions. When a query is received from a user, candidate queries are generated based upon replacing particular words in the query with a transformation of the particular words. Candidate queries are selected that have a high probability of returning relevant results by computing values of the query using language model scoring and translation scoring. The selected candidate queries and the original query are executed to return search results. The search results are displayed to the user with the words in the original query and the transformed words in bold. | 02-26-2009 |
20090132515 | Method and Apparatus for Performing Multi-Phase Ranking of Web Search Results by Re-Ranking Results Using Feature and Label Calibration - A method and apparatus for performing multi-phase ranking of web search results by re-ranking results using feature and label calibration are provided. According to one embodiment of the invention, a ranking function is trained by using machine learning techniques on a set of training samples to produce ranking scores. The ranking function is used to rank the set of training samples according to its ranking score, in order of its relevance to a particular query. Next, a re-ranking function is trained by the same training samples to re-rank the documents from the first ranking. The features and labels of the training samples are calibrated and normalized before they are reused to train the re-ranking function. By this method, training data and training features used in past trainings are leveraged to perform additional training of new functions, without requiring the use of additional training data or features. | 05-21-2009 |
20090182729 | LOCAL QUERY IDENTIFICATION AND NORMALIZATION FOR WEB SEARCH - Computer-implemented methods and systems for processing user entered query data to improve results of a search of pages using a local search database are provided, when searching the internet. The method includes receiving the user entered query data and parsing each word of the query data and examining each word to determine if the word is associated with one of a business name, a city name or a state name. The examining uses probabilistic dictionaries to determine a likelihood that the word is one of the business name, the city name or the state name. Then, associating the words that were determined to be: (i) the business name with a business name tag to create one or more tagged business terms; (ii) the city name with a city name tag to create one or more tagged city terms; and (iii) the state name with a state name tag to create one or more tagged state terms. The method further includes normalizing each of the tagged business terms, the tagged city terms and the tagged state terms. The normalizing includes boosting information if found in the local search database and determining proximity between selected ones of the tagged business, city or state terms. Then, generating an optimized internal search query that incorporates constraints and ranking based on at least the boosting information and the determined proximity between the selected tagged business, city or state terms. The optimized internal search query is applied to the internet to enable search results to be produced and displayed to the user in response to the entered query data. | 07-16-2009 |
20090248595 | NAME VERIFICATION USING MACHINE LEARNING - Computer-enabled methods, apparatus, and computer-readable media are provided for verifying that a given network name, such as a URL, is an official, e.g., registered, approved, or otherwise officially recognized, network name that refers to or identifies a principal, such as a business. These techniques involve receiving a principal name and a given network name, receiving at least one feature attribute from at least one database of feature attributes, wherein the at least one feature attribute comprises a characteristic of the principal name or a characteristic of the network name, and invoking a logistic regression method to generate a probability, based upon the at least one feature attribute, that the given network name is an official network name for the principal name. The logistic regression method may include a gradient boosting tree model that generates the probability based upon the at least one feature attribute. | 10-01-2009 |
20090259629 | ABBREVIATION HANDLING IN WEB SEARCH - A method for handling abbreviations in web queries includes building a dictionary of a plurality of possible word expansions for a plurality of potential abbreviations related to query terms received or anticipated to be received by a search engine; accepting a query including an abbreviation; expanding the abbreviation into one of the plurality of word expansions if a probability that the expansion is correct is above a threshold value, wherein the probability is determined by taking into consideration a context of the abbreviation within the query, wherein the context including at least anchor text; and sending the query with the expanded abbreviation to the search engine to generate a search results page related to the query. | 10-15-2009 |
20090259643 | NORMALIZING QUERY WORDS IN WEB SEARCH - A method for normalizing query words in web search includes populating a dictionary with join and split candidates and corresponding joined and split words from an aggregate of query logs; determining a confidence score for join and split candidates, a highest confidence score for each being characterized in the dictionary as must-join and must-split, respectively; accepting queries with words amenable to being split or joined, or amenable to an addition or deletion of a hyphen or an apostrophe; generating, based on the accepted queries, split candidates obtained from the dictionary, and candidates of join, hyphen, or apostrophe algorithmically; and submitting to a search engine the generated possible candidates characterized as must-join or must-split in the dictionary, to improve search results returned in response to the queries; applying a language dictionary to generated candidates not characterized as must-split or must-join, to rank them, and submitting those highest-ranked to the search engine. | 10-15-2009 |
20100131538 | IDENTIFYING AND EXPANDING IMPLICITLY TEMPORALLY QUALIFIED QUERIES - Methods and apparatus are described for identifying implicitly temporally qualified queries, i.e., queries for which a time period is implied but not explicitly stated, and for expanding such queries to include one or more temporal references. | 05-27-2010 |
20100191758 | SYSTEM AND METHOD FOR IMPROVED SEARCH RELEVANCE USING PROXIMITY BOOSTING - A system and method for improved search relevance using proximity boosting. A query for a web search is received from a user, via a network, wherein the query comprises a plurality of query tokens. One or more concepts are identified in the query wherein each of concepts comprises at least two query tokens. A relative concept strength is determined for each of the identified concepts. The query is then rewritten for submission to a search engine wherein for each of the one or more concepts, a syntax rule associated with the respective relative concept strength of the concept is applied to the query tokens comprising the concept such that the rewritten query represents the one or more concepts whereby the proximity of the one or more concepts in a search result returned by the search engine to the user in response to the rewritten query is boosted. | 07-29-2010 |
20100205198 | SEARCH QUERY DISAMBIGUATION - Disclosed herein is a system and method of query disambiguation. At least one model is generated using training data, which model can be used to score, or rank, possible interpretations identified for a query, which can be used to select an interpretation from a number of possible interpretations. A selected interpretation can be used to process a web search request, e.g., to generate search results that relate to the selected query interpretation, rank or order the items in the search result based on relevance to the selected query interpretation, and/or identify a presentation to be used to display the search results based on the selected query interpretation. | 08-12-2010 |
20100312778 | PREDICTIVE PERSON NAME VARIANTS FOR WEB SEARCH - Techniques for determining when and which name variant candidates to use to re-write a search query that includes a person's name in order to provide the most relevant search results are provided. A determination is made whether a person name is present in a search query request entered by a user. Name variant candidates are generated for each person name. Then, the name variant candidates are ranked for each person name based upon one or more models that calculate a probability value for each name variant candidate. Based upon these rankings, the query may be re-written to include the original person name and a specified number of top ranked name variant candidates to present the user with the most relevant search results. | 12-09-2010 |
20110010353 | ABBREVIATION HANDLING IN WEB SEARCH - A method for handling abbreviations in web queries includes building a dictionary of possible word expansions for potential abbreviations related to query terms received and anticipated to be received by a search engine; accepting a query including an abbreviation from a searching user, where a probability of finding a most probably-correct expansion in the dictionary is a first probability, and a probability that the expansion is the abbreviation itself is a second probability; determining a ratio between the first and second probabilities; expanding the abbreviation in accordance with the most probably-correct expansion when the ratio is above a first threshold value; and highlighting the abbreviation with a suggested expansion of the most probably-correct expansion for the user so that the user may accept the suggested expansion when the ratio is between a second, lower threshold value and the first threshold value. | 01-13-2011 |
20110264647 | QUERY PROCESSING FOR WEB SEARCH - A computer-implemented method for processing user entered query data to improve results of a search of pages using a database, when searching the internet, is disclosed. The method includes receiving the user entered query data and parsing each word of the query data and segmenting words using probability to determine a likelihood that the word is for a particular name. And, associating the particular names with a name tag to create one or more tagged name terms. Then, normalizing each of the tagged name terms and the normalizing including boosting information if found in the database and determining proximity between selected ones of the tagged name terms. The method then generates an optimized search query that incorporates normalized terms and operators. The optimized search query being applied to the internet to enable search results to be produced and displayed to the user in response to the entered query data. | 10-27-2011 |