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    • 2. 发明申请
    • Query Reformulation Using Post-Execution Results Analysis
    • 使用执行后结果分析查询重组
    • US20130086024A1
    • 2013-04-04
    • US13248894
    • 2011-09-29
    • Yi LiuYu ChenQing YuJi-Rong Wen
    • Yi LiuYu ChenQing YuJi-Rong Wen
    • G06F17/30
    • G06F16/951G06F16/3338
    • Systems, methods, devices, and media are described to facilitate the training and employing of a three-class classifier for post-execution search query reformulation. In some embodiments, the classification is trained through a supervised learning process, based on a training set of queries mined from a query log. Query reformulation candidates are determined for each query in the training set, and searches are performed using each reformulation candidate and the un-reformulated training query. The resulting documents lists are analyzed to determine ranking and topic drift features, and to calculate a quality classification. The features and classification for each reformulation candidate are used to train the classifier in an offline mode. In some embodiments, the classifier is employed in an online mode to dynamically perform query reformulation on user-submitted queries.
    • 描述了系统,方法,设备和媒体,以便于训练和采用用于执行后搜索查询重新设计的三类分类器。 在一些实施例中,基于从查询日志挖掘的查询的训练集,通过监督学习过程训练分类。 针对训练集中的每个查询确定查询重写候选,并且使用每个重新配置候选和未重新编排的训练查询执行搜索。 分析结果文件列表以确定排名和主题漂移特征,并计算质量分类。 每个重组候选人的特征和分类用于在离线模式下训练分类器。 在一些实施例中,分类器以在线模式使用以动态地对用户提交的查询进行查询重新配置。