Analysis of topic dynamics of web search
    1.
    发明申请
    Analysis of topic dynamics of web search 审中-公开
    网页搜索的主题动态分析

    公开(公告)号:US20070005646A1

    公开(公告)日:2007-01-04

    申请号:US11171123

    申请日:2005-06-30

    IPC分类号: G06F17/00

    CPC分类号: G06F16/9535 G06F2216/03

    摘要: The subject invention relates to probabilistic models that are trained from transitions among various topics of pages visited by a sample population of search users. In one aspect, probabilistic models of topic transitions are learned for individual users and groups of users. Topic transitions for individuals versus larger groups are analyzed, wherein the relative accuracies of personal models of topic dynamics with models constructed from sets of pages drawn from similar groups and from a larger population of users are compared. To exploit temporal dynamics, the accuracy of these models are tested for predicting transitions in topics of visits at increasingly more distant times in the future. The models can be applied to search topic dynamics of tagged pages, and then utilized to predict topics of subsequent pages visited by users.

    摘要翻译: 本发明涉及由搜索用户的样本群访问的各个主题之间的转换训练的概率模型。 在一个方面,为个人用户和用户组学习主题转换的概率模型。 对个人与较大群体的主题过渡进行了分析,其中比较了主题动态个人模型的相对准确性,以及从较大群体的用户组中绘制的模型构建的模型。 为了利用时间动力学,对这些模型的准确性进行了测试,以预测未来越来越遥远的访问主题的过渡。 这些模型可以应用于搜索标签页面的主题动态,然后用于预测用户访问的后续页面的主题。

    Real time implicit user modeling for personalized search
    2.
    发明授权
    Real time implicit user modeling for personalized search 有权
    用于个性化搜索的实时隐式用户建模

    公开(公告)号:US08442973B2

    公开(公告)日:2013-05-14

    申请号:US11743076

    申请日:2007-05-01

    IPC分类号: G06F7/00 G06F17/00

    CPC分类号: G06F17/30554 G06F17/30867

    摘要: A method and apparatus for utilizing user behavior to immediately modify sets of search results so that the most relevant documents are moved to the top. In one embodiment of the invention, behavior data, which can come from virtually any activity, is used to infer the user's intent. The updated inferred implicit user model is then exploited immediately by re-ranking the set of matched documents to best reflect the information need of the user. The system updates the user model and immediately re-ranks documents at every opportunity in order to constantly provide the most optimal results. In another embodiment, the system determines, based on the similarity of results sets, if the current query belongs in the same information session as one or more previous queries. If so, the current query is expanded with additional keywords in order to improve the targeting of the results.

    摘要翻译: 一种用于利用用户行为立即修改搜索结果集的方法和装置,使得最相关的文档被移动到顶部。 在本发明的一个实施例中,可以使用几乎任何活动的行为数据来推断用户的意图。 然后通过重新排列匹配文档的集合来立即利用更新的推断的隐式用户模型,以最好地反映用户的信息需求。 系统更新用户模型,并在每个机会立即重新排列文档,以不断提供最佳结果。 在另一个实施例中,系统基于结果集的相似性来确定当前查询是否属于与一个或多个先前查询相同的信息会话。 如果是,则使用其他关键字扩展当前查询,以改进结果的定位。

    REAL TIME IMPLICIT USER MODELING FOR PERSONALIZED SEARCH
    3.
    发明申请
    REAL TIME IMPLICIT USER MODELING FOR PERSONALIZED SEARCH 有权
    用于个性化搜索的实时隐含用户建模

    公开(公告)号:US20080114751A1

    公开(公告)日:2008-05-15

    申请号:US11743076

    申请日:2007-05-01

    IPC分类号: G06F7/06

    CPC分类号: G06F17/30554 G06F17/30867

    摘要: A method and apparatus for utilizing user behavior to immediately modify sets of search results so that the most relevant documents are moved to the top. In one embodiment of the invention, behavior data, which can come from virtually any activity, is used to infer the user's intent. The updated inferred implicit user model is then exploited immediately by re-ranking the set of matched documents to best reflect the information need of the user. The system updates the user model and immediately re-ranks documents at every opportunity in order to constantly provide the most optimal results. In another embodiment, the system determines, based on the similarity of results sets, if the current query belongs in the same information session as one or more previous queries. If so, the current query is expanded with additional keywords in order to improve the targeting of the results.

    摘要翻译: 一种用于利用用户行为立即修改搜索结果集的方法和装置,使得最相关的文档被移动到顶部。 在本发明的一个实施例中,可以使用几乎任何活动的行为数据来推断用户的意图。 然后通过重新排列匹配文档的集合来立即利用更新的推断的隐式用户模型,以最好地反映用户的信息需求。 系统更新用户模型,并在每个机会立即重新排列文档,以不断提供最佳结果。 在另一个实施例中,系统基于结果集的相似性来确定当前查询是否属于与一个或多个先前查询相同的信息会话。 如果是,则使用其他关键字扩展当前查询,以改进结果的定位。