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    • 54. 发明申请
    • METHOD AND SYSTEM FOR CLASSIFYING DISPLAY PAGES USING SUMMARIES
    • 使用概要分类显示页的方法和系统
    • US20090119284A1
    • 2009-05-07
    • US12145222
    • 2008-06-24
    • Zheng ChenDou ShenBenyu ZhangHua-Jun ZengWei-Ying Ma
    • Zheng ChenDou ShenBenyu ZhangHua-Jun ZengWei-Ying Ma
    • G06F7/06G06F17/30
    • G06F16/345G06F16/951
    • 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.
    • 一种基于自动生成的显示页面摘要来分类显示页面的方法和系统。 网页分类系统使用网页摘要系统来生成网页摘要。 网页的摘要可以包括与网页的主要主题最密切相关的网页的句子。 总结系统可以结合多个汇总技术的优点来识别代表网页的主要主题的网页的句子。 一旦生成摘要,分类系统可以将常规分类技术应用于摘要以对网页进行分类。 分类系统可以使用诸如朴素贝叶斯分类器或支持向量机的常规分类技术来基于由汇总系统生成的摘要来识别网页的分类。
    • 59. 发明授权
    • Verifying relevance between keywords and web site contents
    • 验证关键字和网站内容之间的相关性
    • US07260568B2
    • 2007-08-21
    • US10826162
    • 2004-04-15
    • Benyu ZhangHua-Jun ZengZheng ChenWei-Ying MaLi LiYing LiTarek Najm
    • Benyu ZhangHua-Jun ZengZheng ChenWei-Ying MaLi LiYing LiTarek Najm
    • G06F17/30
    • G06F17/30687G06F17/30663Y10S707/99933Y10S707/99934Y10S707/99935
    • Systems and methods for verifying relevance between terms and Web site contents are described. In one aspect, site contents from a bid URL are retrieved. Expanded term(s) semantically and/or contextually related to bid term(s) are calculated. Content similarity and expanded similarity measurements are calculated from respective combinations of the bid term(s), the site contents, and the expanded terms. Category similarity measurements between the expanded terms and the site contents are determined in view of a trained similarity classifier. The trained similarity classifier having been trained from mined web site content associated with directory data. A confidence value providing an objective measure of relevance between the bid term(s) and the site contents is determined from the content, expanded, and category similarity measurements evaluating the multiple similarity scores in view of a trained relevance classifier model.
    • 描述了用于验证术语和网站内容之间的相关性的系统和方法。 一方面,检索出价网址中的网站内容。 计算语法上和/或与投标期相关的扩展术语。 内容相似性和扩展的相似度测量是根据投标条件,站点内容和扩展条款的各自组合计算的。 考虑到经过训练的相似性分类器,确定扩展术语和站点内容之间的类别相似度测量。 经过训练的相似性分类器已经从与目录数据相关联的挖掘的网站内容训练。 考虑到训练有素的相关性分类器模型,从评估多重相似度分数的内容,扩展和类别相似度测度中确定提供投标项和站点内容之间的相关性的客观量度的置信度值。