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    • 1. 发明授权
    • Probablistic models and methods for combining multiple content classifiers
    • 用于组合多个内容分类器的概念模型和方法
    • US07107254B1
    • 2006-09-12
    • US09850172
    • 2001-05-07
    • Susan T. DumaisEric J. HorvitzPaul Nathan Bennett
    • Susan T. DumaisEric J. HorvitzPaul Nathan Bennett
    • G06N5/02
    • G06N7/005
    • The invention applies a probabilistic approach to combining evidence regarding the correct classification of items. Training data and machine learning techniques are used to construct probabilistic dependency models that effectively utilize evidence. The evidence includes the outputs of one or more classifiers and optionally one or more reliability indicators. The reliability indicators are, in a broad sense, attributes of the items being classified. These attributes can include characteristics of an item, source of an item, and meta-level outputs of classifiers applied to the item. The resulting models include meta-classifiers, which combine evidence from two or more classifiers, and tuned classifiers, which use reliability indicators to inform the interpretation of classical classifier outputs. The invention also provides systems and methods for identifying new reliability indicators.
    • 本发明应用概率方法来合并关于项目正确分类的证据。 训练数据和机器学习技术用于构建有效利用证据的概率依赖模型。 证据包括一个或多个分类器的输出和可选的一个或多个可靠性指标。 在广义上,可靠性指标是被归类的物品的属性。 这些属性可以包括项目的特征,项目的来源以及应用于项目的分类器的元级输出。 所得到的模型包括组合来自两个或更多个分类器的证据的分类器和使用可靠性指标来通知经典分类器输出的解释的调谐分类器。 本发明还提供用于识别新的可靠性指标的系统和方法。
    • 7. 发明授权
    • Systems and methods for performing background queries from content and activity
    • 用于从内容和活动执行后台查询的系统和方法
    • US07225187B2
    • 2007-05-29
    • US10827920
    • 2004-04-20
    • Susan T. DumaisEric J. HorvitzEdward B. CutrellRaman K. Sarin
    • Susan T. DumaisEric J. HorvitzEdward B. CutrellRaman K. Sarin
    • G06F17/30
    • G06F17/30867G06F17/30613Y10S707/99935
    • Most information retrieval systems start with a user's explicit query. Systems and methods are provided that perform implicit or background queries to one or more information sources based on the ongoing activities of users. The methods provide users with the results of such automated contextualized searches in an unobtrusive manner. In one aspect, implicit queries are run when users are reading, working on or composing an application. Queries can be automatically generated by analyzing an application, and results can be presented in a variety of peripheral display configurations, including a small pane adjacent to a current window to provide peripheral awareness of related information that is automatically determined from existing user context and/or related content from the application. The invention includes methods for building models that predict the value of different queries, and of the results generated by such queries, based on logged data, and for using such models to control query formulation and to mediate decisions about displaying the results of implicit queries.
    • 大多数信息检索系统从用户的显式查询开始。 提供了系统和方法,其基于用户正在进行的活动,对一个或多个信息源执行隐式或后台查询。 这些方法以不引人注目的方式为用户提供了这种自动化的语境化搜索的结果。 在一个方面,当用户阅读,处理或撰写应用程序时,会运行隐式查询。 可以通过分析应用程序自动生成查询,结果可以呈现在各种外围显示配置中,包括与当前窗口相邻的小窗格,以提供从现有用户上下文自动确定的相关信息的周边感知和/或 相关内容从应用程序。 本发明包括用于构建基于记录数据来预测不同查询的价值以及由这些查询产生的结果的模型的方法,以及使用这些模型来控制查询表达并调解关于显示隐式查询的结果的决策。