| Patent application number | Description | Published |
|---|
| 20080222125 | ANALYZING A QUERY LOG FOR USE IN MANAGING CATEGORY-SPECIFIC ELECTRONIC CONTENT - Providing category-specific electronic content includes receiving a request for electronic content. The request has an attribute. The attribute of the received request is compared to an attribute related to a query included in a log of search queries. An indication of a category that represents a search query from a log of search queries that is related to an attribute that matches the attribute of the received request is accessed, and electronic content that is representative of the identified category is accessed and provided. | 09-11-2008 |
| 20080319995 | RELIABILITY OF DUPLICATE DOCUMENT DETECTION ALGORITHMS - In a single-signature duplicate document system, a secondary set of attributes is used in addition to a primary set of attributes so as to improve the precision of the system. When the projection of a document onto the primary set of attributes is below a threshold, then a secondary set of attributes is used to supplement the primary lexicon so that the projection is above the threshold. | 12-25-2008 |
| 20090222444 | QUERY DISAMBIGUATION - A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query. | 09-03-2009 |
| 20100088322 | REAL TIME QUERY TRENDS WITH MULTI-DOCUMENT SUMMARIZATION - A list of “hot topics” may be provided to a user to indicate information that is currently popular. A topic may be deemed popular when a large number of search queries related to the topic are entered by users. A search system may receive and analyze an electronic source of published information to determine a reason for why a particular popular topic is popular. If content related to why a particular popular topic is popular exists in multiple electronic sources of published information, text summarization techniques may be used to determine a reason for why the popular topic is popular by from among the multiple electronic sources of published information. | 04-08-2010 |
| 20100169329 | SYSTEM FOR SIMILAR DOCUMENT DETECTION - A document is compared to the documents in a document collection using a hash algorithm and collection statistics to detect if the document is similar to any of the documents in the document collection. | 07-01-2010 |
| 20100235375 | TEMPORAL SEARCH QUERY PERSONALIZATION - A user is made able to configure a search query to be responsive to temporal factors in order to adjust the search query to more accurately reflect the user's true information need. By adjusting the search query in this way, the user is more likely to receive satisfactory search results. | 09-16-2010 |
| 20100299290 | Web Query Classification - A query phrase may be automatically classified to one or more topics of interest (e.g., categories) to assist in routing the query phrase to one or more appropriate backend databases. A selectional preference query classification technique may be used to classify the query phrase based on a comparison between the query phrase and patterns of query phrases. Additionally, or alternatively, a combination of query classification techniques may be used to classify the query phrase. Topical classification of a query phrase also may be used to assist a search system in delivering auxiliary information to a user who entered the query phrase. Advertisements, for instance, may be tailored based on classification rather than query keywords. | 11-25-2010 |
