| Patent application number | Description | Published |
|---|
| 20080215561 | SCORING RELEVANCE OF A DOCUMENT BASED ON IMAGE TEXT - A method and system for determining relevance of a document having text and images to a text string is provided. A scoring system identifies image text associated with an image of the document. The scoring system calculates an image score indicating relevance of the image text to the text string. The image score may be used in many applications, such as searching, summary generation, and document classification, image search, and image classification. | 09-04-2008 |
| 20090024607 | QUERY SELECTION FOR EFFECTIVELY LEARNING RANKING FUNCTIONS - A learning system for a search ranking function model may include a computer program that iteratively refines the model using new queries and associated documents from an unlabeled training set. The unlabeled training set may include a set of queries for which the associated documents have not been labeled as “relevant” or otherwise labeled. The new queries may be selected based on a similarity to and an accuracy of each neighbor from a labeled training set, such as a labeled validation set. Upon selection, the documents associated with the new queries may be labeled. The new queries and their associated documents may be accumulated into a labeled training set, such as a labeled training set, and a refined model may be learned based on the augmented labeled training set. The model may be iteratively refined until it is determined that the model is adequate. | 01-22-2009 |
| 20090100005 | MAPPING NETWORK ADDRESSES TO GEOGRAPHICAL LOCATIONS - A network address mapping system is described. The network address mapping system can identify a set of Web pages, collects information from the Web pages indicating geographical locations (“geolocations”), and correlate the geolocations with the network addresses from which the identified Web pages are served. The collected information can be weighted based on various factors, such as its relative position in a Web page. The collected information can then be used to identify a geolocation. The network mapping system can deduce geolocations for portions of ranges of network addresses based on the score, and can infer geolocations for other portions based on the deduced geolocations. This mapping can then be stored in a database and provided as a geomapping service. The network address mapping system is able to map network addresses to geographical locations. Thereafter, when a user's client computing device accesses a Web server, the Web server can easily and accurately determine a geographical location by querying the database storing the mapping or a geomapping service. | 04-16-2009 |
| 20090327264 | Topics in Relevance Ranking Model for Web Search - Described is a technology by which topics corresponding to web pages are used in relevance ranking of those pages. Topics are extracted from each web page of a set of web pages that are found via a query. For example, text such as nouns may be extracted from the title, anchor texts and URL of a page, and used as the topics. The extracted topics from a page are used to compute a relevance score for that page based on an evaluation of that page's topics against the query. The pages are then ranked relative to one another based at least in part on the relevance score computed for each page, such as by determining a matching level for each page, ranking pages by each level, and ranking pages within each level. Also described is training a model to perform the relevance scoring and/or ranking. | 12-31-2009 |
| 20110078131 | EXPERIMENTAL WEB SEARCH SYSTEM - Described is the running of search-related experiments on a full (or partial) offline snapshot copy of the search engine documents of an actual production system. A snapshot experimentation subsystem runs experimental code related to web searches on the offline data, including to run experimental index building code to build an experimental index (e.g., to test a new document feature), and/or to run experimental search-related code, such as to rank search results according to experimental ranking code, to implement an experimental search strategy, and/or to generate experimental captions. | 03-31-2011 |
| 20110087660 | SCORING RELEVANCE OF A DOCUMENT BASED ON IMAGE TEXT - A method and system for determining relevance of a document having text and images to a text string is provided. A scoring system identifies image text associated with an image of the document. The scoring system calculates an image score indicating relevance of the image text to the text string. The image score may be used in many applications, such as searching, summary generation, and document classification, image search, and image classification. | 04-14-2011 |
| 20110137886 | Data-Centric Search Engine Architecture - Described is a data-centric web search engine technology/architecture, in which document metadata, including offline-extracted metadata, is used as part of a search indexing and ranking pipeline. A web data management component receives crawled documents and extracts document metadata from the documents. An indexing component uses the document metadata to build an index for the documents. A serving component uses the index and the document metadata to serve content, e.g., search results. Also described is the use of query metadata extracted from queries of a query log for use in the pipeline. | 06-09-2011 |
| 20120030200 | TOPICS IN RELEVANCE RANKING MODEL FOR WEB SEARCH - Described is a technology by which topics corresponding to web pages are used in relevance ranking of those pages. Topics are extracted from each web page of a set of web pages that are found via a query. For example, text such as nouns may be extracted from the title, anchor texts and URL of a page, and used as the topics. The extracted topics from a page are used to compute a relevance score for that page based on an evaluation of that page's topics against the query. The pages are then ranked relative to one another based at least in part on the relevance score computed for each page, such as by determining a matching level for each page, ranking pages by each level, and ranking pages within each level. Also described is training a model to perform the relevance scoring and/or ranking. | 02-02-2012 |
