Abstract: A method and system for classifying display pages based on automatically generated summaries of display pages. A web page classification system uses a web page summarization system to generate summaries of web pages. The summary of a web page may include the sentences of the web page that are most closely related to the primary topic of the web page. The summarization system may combine the benefits of multiple summarization techniques to identify the sentences of a web page that represent the primary topic of the web page. Once the summary is generated, the classification system may apply conventional classification techniques to the summary to classify the web page. The classification system may use conventional classification techniques such as a Naïve Bayesian classifier or a support vector machine to identify the classifications of a web page based on the summary generated by the summarization system.

Abstract: A method and system for classifying display pages based on automatically generated summaries of display pages. A web page classification system uses a web page summarization system to generate summaries of web pages. The summary of a web page may include the sentences of the web page that are most closely related to the primary topic of the web page. The summarization system may combine the benefits of multiple summarization techniques to identify the sentences of a web page that represent the primary topic of the web page. Once the summary is generated, the classification system may apply conventional classification techniques to the summary to classify the web page. The classification system may use conventional classification techniques such as a Naïve Bayesian classifier or a support vector machine to identify the classifications of a web page based on the summary generated by the summarization system.

Abstract: Described is a technology by which an intermediate taxonomy is processed (e.g., offline) with respect to a target taxonomy to determine relationship values between categories represented in the intermediate taxonomy and the target taxonomy. The relationship values are used to construct a bridging classifier for use in online query processing to relate queries to categories in the target taxonomy. The relation is based on each target category's relationship to one or more categories that were represented in the intermediate taxonomy. Further, only a relevant subset of the categories represented in the intermediate taxonomy may be chosen for use in the bridging classifier, e.g., based on relative probability scores and/or mutual information scores computed between the categories represented in the intermediate taxonomy and categories in the target taxonomy.

Abstract: Methods and systems are provided for performing a comparative search. In one example, the comparative search is performed over a network, such as the web, or a database. In one exemplary implementation, a user transmits a plurality of queries which represent the topics that a user wants to compare, and a computing system can automatically retrieve and rank web pages or documents based on both their relevance to queries and the comparative contents they contain. In one such example, the comparative pages are displayed in a pair or other form of a grouping. In another example, comparative results having similar contents may be clustered into meaningful themes.

Abstract: A method and system for calculating the significance of a sentence within a document is provided. The summarization system calculates the significance of the sentences of a document and selects the most significant sentences as the summary of the document. The summarization system calculates the significance of a sentence based on the “important” words of the document that are contained within the sentence. The summarization system calculates the importance of words of the document using various scoring techniques and then combines the scores to classify a word as important or not important. The summarization system can then be used to identify significant sentences of the document based on the important words that a sentence contains and select significant sentences as a summary of the document.

Abstract: A method and system for classifying display pages based on automatically generated summaries of display pages. A web page classification system uses a web page summarization system to generate summaries of web pages. The summary of a web page may include the sentences of the web page that are most closely related to the primary topic of the web page. The summarization system may combine the benefits of multiple summarization techniques to identify the sentences of a web page that represent the primary topic of the web page. Once the summary is generated, the classification system may apply conventional classification techniques to the summary to classify the web page. The classification system may use conventional classification techniques such as a Naïve Bayesian classifier or a support vector machine to identify the classifications of a web page based on the summary generated by the summarization system.