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公开(公告)号：US20130060763A1
公开(公告)日：2013-03-07
申请号：US13225583
申请日：2011-09-06
申请人： Sebastian de la Chica , Kevyn B. Collins-Thompson , Paul N. Bennett , David Alexander Sontag , Ryen W. White
发明人： Sebastian de la Chica , Kevyn B. Collins-Thompson , Paul N. Bennett , David Alexander Sontag , Ryen W. White
IPC分类号： G06F17/30
CPC分类号： G06F17/30867 , G06F17/27 , G06F17/3053 , G06F17/30699
摘要： A request can be received and a request reading level representation for the request can be inferred. In response to the request, the request reading level representation can be compared with one or more reading difficulty level representations for one or more response items. Also in response to the request, one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items can be returned. The indication(s) may include a ranking of the response items. The ranking can be based at least in part on a request reading level representation for the query and reading difficulty level representations for the response items. The response item(s) may also be returned.
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公开(公告)号：US08954423B2
公开(公告)日：2015-02-10
申请号：US13225583
申请日：2011-09-06
申请人： Sebastian de la Chica , Kevyn B. Collins-Thompson , Paul N. Bennett , David Alexander Sontag , Ryen W. White
发明人： Sebastian de la Chica , Kevyn B. Collins-Thompson , Paul N. Bennett , David Alexander Sontag , Ryen W. White
CPC分类号： G06F17/30867 , G06F17/27 , G06F17/3053 , G06F17/30699
摘要： A request can be received and a request reading level representation for the request can be inferred. In response to the request, the request reading level representation can be compared with one or more reading difficulty level representations for one or more response items. Also in response to the request, one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items can be returned. The indication(s) may include a ranking of the response items. The ranking can be based at least in part on a request reading level representation for the query and reading difficulty level representations for the response items. The response item(s) may also be returned.
摘要翻译： 可以接收到请求，并且可以推断出请求的请求读取级别表示。 响应于该请求，可以将请求读取级别表示与一个或多个响应项目的一个或多个读取难度级别表示进行比较。 还响应于该请求，可以返回将请求读取级别表示与一个或多个响应项目的一个或多个读取难度级别表示进行比较的结果的一个或多个指示。 指示可以包括响应项目的排名。 排名可以至少部分地基于用于响应项目的查询的请求读取级别表示和读取难度级别表示。 还可以返回响应项目。
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公开(公告)号：US20120323828A1
公开(公告)日：2012-12-20
申请号：US13162906
申请日：2011-06-17
申请人： David A. Sontag , Kevyn B. Collins-Thompson , Paul N. Bennett , Ryen W. White , Susan T. Dumais
发明人： David A. Sontag , Kevyn B. Collins-Thompson , Paul N. Bennett , Ryen W. White , Susan T. Dumais
CPC分类号： G06F17/30011
摘要： A query processing system is described herein for personalizing results for a particular user. The query processing system operates by receiving a query from a particular user u who intends to find results that satisfy the query with respect to a topic Tu, the user being characterized by user information θu. In one implementation, the query processing system then produces a generic topic distribution Prr(T|q) associated with the query that is germane to a population of generic users, as well as a user-specific query-dependent topic distribution Pr(Tu|q,θu) for the particular user. The query processing system then produces personalized results for the particular user based on Prr(T|q) and Pr(Tu|q,θu). The query processing system can use multiple techniques to produce Pr(Tu|q,θu), such as, in one approach, a discriminative learning approach.
摘要翻译： 这里描述了一种用于个性化特定用户的结果的查询处理系统。 查询处理系统通过接收来自特定用户的查询，该用户u意图找到满足关于主题Tu的查询的结果，该用户由用户信息和图标表征; u。 在一个实现中，查询处理系统然后产生与查询相关联的通用主题分布Prr（T | q），该查询与普通用户的总体以及用户特定的查询相关主题分布Pr（Tu | q，＆thetas; u）对于特定用户。 然后，查询处理系统基于Prr（T | q）和Pr（Tu | q，＆thetas; u）产生针对特定用户的个性化结果。 查询处理系统可以使用多种技术来产生Pr（Tu | q，＆amp; tt; u），例如在一种方法中的歧视性学习方法。
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公开(公告)号：US08700544B2
公开(公告)日：2014-04-15
申请号：US13162906
申请日：2011-06-17
申请人： David A. Sontag , Kevyn B. Collins-Thompson , Paul N. Bennett , Ryen W. White , Susan T. Dumais
发明人： David A. Sontag , Kevyn B. Collins-Thompson , Paul N. Bennett , Ryen W. White , Susan T. Dumais
CPC分类号： G06F17/30011
摘要： A query processing system is described herein for personalizing results for a particular user. The query processing system operates by receiving a query from a particular user u who intends to find results that satisfy the query with respect to a topic Tu, the user being characterized by user information θu. In one implementation, the query processing system then produces a generic topic distribution Prr(T|q) associated with the query that is germane to a population of generic users, as well as a user-specific query-dependent topic distribution Pr(Tu|q,θu) for the particular user. The query processing system then produces personalized results for the particular user based on Prr(T|q) and Pr(Tu|q,θu). The query processing system can use multiple techniques to produce Pr(Tu|q,θu), such as, in one approach, a discriminative learning approach.
摘要翻译： 这里描述了一种用于个性化特定用户的结果的查询处理系统。 查询处理系统通过接收来自特定用户的查询，该用户u意图找到满足关于主题Tu的查询的结果，该用户由用户信息和图标表征; u。 在一个实现中，查询处理系统然后产生与查询相关联的通用主题分布Prr（T | q），该查询与普通用户的总体以及用户特定的查询相关主题分布Pr（Tu | q，＆thetas; u）对于特定用户。 然后，查询处理系统基于Prr（T | q）和Pr（Tu | q，＆thetas; u）产生针对特定用户的个性化结果。 查询处理系统可以使用多种技术来产生Pr（Tu | q，＆amp; tt; u），例如在一种方法中的歧视性学习方法。
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公开(公告)号：US08719249B2
公开(公告)日：2014-05-06
申请号：US12464496
申请日：2009-05-12
申请人： Paul N. Bennett , David Maxwell Chickering , Kevyn B. Collins-Thompson , Susan Dumais , Daniel J. Liebling
发明人： Paul N. Bennett , David Maxwell Chickering , Kevyn B. Collins-Thompson , Susan Dumais , Daniel J. Liebling
IPC分类号： G06F17/30
CPC分类号： G06F17/30707
摘要： One or more systems and/or techniques are provided for constructing a query classification index that can be used to classify a query into relevant categories. Where documents in an index are classified into one or more category predictions for a category hierarchy, classification metadata is generated for categories to which a document in the index has been classified. Further, the classification metadata is associated to the corresponding documents in the index. Additionally, a query of the index can be classified using the metadata associated to the documents in the index, and query results can be provided that are classified by the one or more categories identified by the classification of the query.
摘要翻译： 提供了一种或多种系统和/或技术来构建可用于将查询分类为相关类别的查询分类索引。 如果索引中的文档被分类为类别层次结构的一个或多个类别预测，则为索引中的文档分类的类别生成分类元数据。 此外，分类元数据与索引中的相应文档相关联。 此外，可以使用与索引中的文档相关联的元数据来分类索引的查询，并且可以提供由通过查询的分类识别的一个或多个类别分类的查询结果。
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公开(公告)号：US09535995B2
公开(公告)日：2017-01-03
申请号：US13323845
申请日：2011-12-13
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： Technologies are described herein that pertain to optimizing a ranker component for a risk-oriented objective. Various definitions of risk are described herein, wherein risk is based upon variance in performance scores assigned to the ranker component for respective queries in a data store. Additionally, risk is optionally based upon variance in relative performance of the ranker component versus a baseline ranker component.
摘要翻译： 本文描述了涉及为风险导向目标优化游标组件的技术。 这里描述了风险的各种定义，其中风险基于分配给数据存储器中的各个查询的分数器组件的性能评分的差异。 另外，风险可选地基于排队组件相对于基线限制器组件的相对性能的变化。
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公开(公告)号：US20130151495A1
公开(公告)日：2013-06-13
申请号：US13323845
申请日：2011-12-13
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： Technologies are described herein that pertain to optimizing a ranker component for a risk-oriented objective. Various definitions of risk are described herein, wherein risk is based upon variance in performance scores assigned to the ranker component for respective queries in a data store. Additionally, risk is optionally based upon variance in relative performance of the ranker component versus a baseline ranker component.
摘要翻译： 本文描述了涉及为风险导向目标优化游标组件的技术。 这里描述了风险的各种定义，其中风险基于分配给数据存储器中的各个查询的分数器组件的性能评分的差异。 另外，风险可选地基于排队组件相对于基线限制器组件的相对性能的变化。
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公开(公告)号：US20120233140A1
公开(公告)日：2012-09-13
申请号：US13043500
申请日：2011-03-09
申请人： Kevyn B. Collins-Thompson , Ni Lao
发明人： Kevyn B. Collins-Thompson , Ni Lao
IPC分类号： G06F17/30
CPC分类号： G06F16/3338
摘要： A model generation module is described herein for using a machine learning technique to generate a model for use by a search engine. The model assists the search engine in generating alterations of search queries, so as to improve the relevance and performance of the search queries. The model includes a plurality of features having weights and levels of uncertainty associated therewith, where each feature defines a rule for altering a search query in a defined manner when a context condition, specified by the rule, is present. The model generation module generates the model based on user behavior information, including query reformulation information and user preference information. The query reformulation information indicates query reformulations made by at least one agent (such as users). The preference information indicates at extent to which the users were satisfied with the query reformulations.
摘要翻译： 本文描述了使用机器学习技术来生成由搜索引擎使用的模型的模型生成模块。 该模型帮助搜索引擎生成搜索查询的更改，以提高搜索查询的相关性和性能。 该模型包括具有与其相关联的权重和不确定级别的多个特征，其中每个特征定义了当由规则指定的上下文条件存在时以定义的方式改变搜索查询的规则。 模型生成模块基于用户行为信息生成模型，包括查询重构信息和用户偏好信息。 查询重写信息指示由至少一个代理（诸如用户）进行的查询重新制定。 偏好信息表示用户对查询重新设计感到满意的程度。
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