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公开(公告)号：US07685099B2
公开(公告)日：2010-03-23
申请号：US11770445
申请日：2007-06-28
申请人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06Q30/02
摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.
摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测时间无关查询的频率，查询分析系统随时间分析查询的频率，以识别频率的显着增加，这被称为“查询事件”或“事件”。查询分析系统预测频率 基于具有事件倾向于在要预测的查询的事件之前的查询的与时间无关的查询。
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公开(公告)号：US08838512B2
公开(公告)日：2014-09-16
申请号：US13089103
申请日：2011-04-18
申请人： Jun Yan , Ning Liu , Lei Ji , Zheng Chen
发明人： Jun Yan , Ning Liu , Lei Ji , Zheng Chen
CPC分类号： G06F17/30864
摘要： A classification process may reduce the computational resources and time required to collect and classify training data utilized to enable a user to effectively access online information. According to some implementations, training data is established by defining one or more seed queries and query patterns. A bi-partite graph may be constructed using the seed query and query pattern information. A traversal of the bi-partite graph can be performed to expand the training data to encompass sufficient data to perform classification of the present search task.
摘要翻译： 分类过程可以减少收集和分类用于使用户有效访问在线信息的训练数据所需的计算资源和时间。 根据一些实施方式，通过定义一个或多个种子查询和查询模式来建立训练数据。 可以使用种子查询和查询模式信息来构建双分图。 可以执行双分图的遍历以扩展训练数据以包括足够的数据来执行本次搜索任务的分类。
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公开(公告)号：US20130246435A1
公开(公告)日：2013-09-19
申请号：US13419690
申请日：2012-03-14
申请人： Jun Yan , Lei Ji , Edward W. Wild , Yi Li , Ning Liu , Zheng Chen
发明人： Jun Yan , Lei Ji , Edward W. Wild , Yi Li , Ning Liu , Zheng Chen
IPC分类号： G06F17/30
CPC分类号： G06F16/355
摘要： A knowledge extraction framework may iteratively enrich an ontology that is used to classify structured knowledge obtained from web pages based on structured knowledge previously acquired from other web pages. The framework may enable a user to define the ontology for extracting structured knowledge from a plurality of web pages. The framework applies the ontology using a supervised extraction algorithm to extract seed information from a set of web pages. The framework further applies an unsupervised extraction algorithm to extract the structured knowledge from an additional set of web pages. The framework subsequently maps the structured knowledge to the ontology based on the seed information to enrich the ontology.
摘要翻译： 知识提取框架可以迭代地丰富用于基于先前从其他网页获取的结构化知识对从网页获得的结构化知识进行分类的本体。 框架可以使用户能够定义用于从多个网页提取结构化知识的本体。 该框架使用监督提取算法应用本体，从一组网页中提取种子信息。 该框架进一步应用无监督提取算法从一组额外的网页提取结构化知识。 该框架随后基于种子信息将结构化知识映射到本体，以丰富本体。
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公开(公告)号：US20120284224A1
公开(公告)日：2012-11-08
申请号：US13100305
申请日：2011-05-04
申请人： Jun Yan , Lei Ji , Ning Liu , Zhimin Zhang , Zheng Chen
发明人： Jun Yan , Lei Ji , Ning Liu , Zhimin Zhang , Zheng Chen
IPC分类号： G06F17/30
CPC分类号： G06F16/951
摘要： Architecture that defines domain knowledge on networks, such as the Internet, as tables where each row is an entity in the target domain and each column is an attribute of these entities. The corresponding values for entity-attribute pairs are the domain knowledge. The architecture provides semi-automatic and systematic ways to extract network knowledge from at least an unstructured and semi-structured network (the Internet), structuralizes the knowledge in table format, and uses the domain tables to build the online updated knowledge base.
摘要翻译： 在网络上定义领域知识（例如Internet）的架构，作为每个行是目标域中的实体的表，每列是这些实体的属性。 实体 - 属性对的相应值是域知识。 该架构提供半自动和系统的方法，从至少一个非结构化和半结构化网络（Internet）中提取网络知识，将表格格式的知识结构化，并使用域表构建在线更新的知识库。
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公开(公告)号：US08239334B2
公开(公告)日：2012-08-07
申请号：US12344093
申请日：2008-12-24
申请人： Jun Yan , Ning Liu , Lei Ji , Zheng Chen
发明人： Jun Yan , Ning Liu , Lei Ji , Zheng Chen
CPC分类号： G06F17/30675
摘要： A tool facilitating learning latent semantics for ranking (LLSR) tailored to the ranking task via leveraging relevance information of query-document pairs to learn a tailored latent semantic space such that other documents are better ranked for the queries in the subspace. The tool applying a learning latent semantics for ranking algorithm integrating LLSR, thereby enabling learning an optimal latent semantic space (LSS) for ranking by utilizing relevance information in the training process of subspace learning. The tool enabling an optimization of the LSS as a closed form solution and facilitating reporting the learned LSS.
摘要翻译： 一种通过利用查询文档对的相关性信息来学习定制的潜在语义空间，使其他文档更好地排列在子空间中的查询的方法，帮助学习用于排名任务的潜在语义（LLSR）。 该工具应用学习潜在语义用于整合LLSR的排序算法，从而通过在子空间学习的训练过程中利用相关性信息来学习优化潜在语义空间（LSS）进行排名。 该工具可以将LSS优化为封闭式解决方案，并有助于报告所学习的LSS。
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公开(公告)号：US20110077998A1
公开(公告)日：2011-03-31
申请号：US12568707
申请日：2009-09-29
申请人： Jun Yan , Ning Liu , Lei Ji , Dong Zhuang , Zheng Chen
发明人： Jun Yan , Ning Liu , Lei Ji , Dong Zhuang , Zheng Chen
CPC分类号： G06Q30/02
摘要： A method for categorizing online user behavior data, including creating a target set of users based on an advertiser query, identifying two or more users in the target set having one or more first similar behavior attributes using a Minhash algorithm; and modifying the target set according to the two or more identified users.
摘要翻译： 一种用于对在线用户行为数据进行分类的方法，包括基于广告商查询创建目标用户集合，使用Minhash算法识别具有一个或多个第一相似行为属性的目标集合中的两个或多个用户; 以及根据所述两个或多个识别的用户修改所述目标集合。
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公开(公告)号：US07693823B2
公开(公告)日：2010-04-06
申请号：US11770385
申请日：2007-06-28
申请人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06Q30/02
摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.
摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测时间无关查询的频率，查询分析系统随时间分析查询的频率，以识别频率的显着增加，这被称为“查询事件”或“事件”。查询分析系统预测频率 基于具有事件倾向于在要预测的查询的事件之前的查询的与时间无关的查询。
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公开(公告)号：US07689622B2
公开(公告)日：2010-03-30
申请号：US11770423
申请日：2007-06-28
申请人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06Q30/02
摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.
摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测时间无关查询的频率，查询分析系统随时间分析查询的频率，以识别频率的显着增加，这被称为“查询事件”或“事件”。查询分析系统预测频率 基于具有事件倾向于在要预测的查询的事件之前的查询的与时间无关的查询。
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公开(公告)号：US20090006284A1
公开(公告)日：2009-01-01
申请号：US11770445
申请日：2007-06-28
申请人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
CPC分类号： G06F17/30864 , G06Q30/02
摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.
摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测与时间无关的查询的频率，查询分析系统会随着时间的推移分析查询的频率，以确定频率的显着增加，这被称为“查询事件”或“事件”。 查询分析系统基于具有事件倾向于在要预测的查询的事件之前的查询来预测与时间无关的查询的频率。
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公开(公告)号：US20090006045A1
公开(公告)日：2009-01-01
申请号：US11770385
申请日：2007-06-28
申请人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Ning Liu , Jun Yan , Benyu Zhang , Zheng Chen , Jian Wang
IPC分类号： G06F17/10
CPC分类号： G06F17/30864 , G06Q30/02
摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.
摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测与时间无关的查询的频率，查询分析系统会随着时间的推移分析查询的频率，以确定频率的显着增加，这被称为“查询事件”或“事件”。 查询分析系统基于具有事件倾向于在要预测的查询的事件之前的查询来预测与时间无关的查询的频率。
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