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    • 1. 发明授权
    • Document characterization using a tensor space model
    • 文档表征使用张量空间模型
    • US07529719B2
    • 2009-05-05
    • US11378095
    • 2006-03-17
    • Ning LiuBenyu ZhangJun YanZheng ChenHua-Jun ZengJian Wang
    • Ning LiuBenyu ZhangJun YanZheng ChenHua-Jun ZengJian Wang
    • G06N5/00
    • G06N5/02G06F17/30705
    • Computer-readable media having computer-executable instructions and apparatuses categorize documents or corpus of documents. A Tensor Space Model (TSM), which models the text by a higher-order tensor, represents a document or a corpus of documents. Supported by techniques of multilinear algebra, TSM provides a framework for analyzing the multifactor structures. TSM is further supported by operations and presented tools, such as the High-Order Singular Value Decomposition (HOSVD) for a reduction of the dimensions of the higher-order tensor. The dimensionally reduced tensor is compared with tensors that represent possible categories. Consequently, a category is selected for the document or corpus of documents. Experimental results on the dataset for 20 Newsgroups suggest that TSM is advantageous to a Vector Space Model (VSM) for text classification.
    • 具有计算机可执行指令和设备的计算机可读介质将文档或语料库分类。 张量空间模型(TSM),其通过高阶张量对文本进行建模,表示文档或文档语料库。 由多线代数技术支持,TSM为多因素结构分析提供了框架。 TSM还受到操作和提出的工具的支持,例如用于降低高阶张量尺寸的高阶奇异值分解(HOSVD)。 将尺寸减小的张量与表示可能类别的张量进行比较。 因此,文档或文档的语料库选择一个类别。 20个新闻组的数据集的实验结果表明,TSM对于文本分类的向量空间模型(VSM)是有利的。
    • 2. 发明申请
    • Document characterization using a tensor space model
    • 文档表征使用张量空间模型
    • US20070239643A1
    • 2007-10-11
    • US11378095
    • 2006-03-17
    • Ning LiuBenyu ZhangJun YanZheng ChenHua-Jun ZengJian Wang
    • Ning LiuBenyu ZhangJun YanZheng ChenHua-Jun ZengJian Wang
    • G06N3/00
    • G06N5/02G06F17/30705
    • Computer-readable media having computer-executable instructions and apparatuses categorize documents or corpus of documents. A Tensor Space Model (TSM), which models the text by a higher-order tensor, represents a document or a corpus of documents. Supported by techniques of multilinear algebra, TSM provides a framework for analyzing the multifactor structures. TSM is further supported by operations and presented tools, such as the High-Order Singular Value Decomposition (HOSVD) for a reduction of the dimensions of the higher-order tensor. The dimensionally reduced tensor is compared with tensors that represent possible categories. Consequently, a category is selected for the document or corpus of documents. Experimental results on the dataset for 20 Newsgroups suggest that TSM is advantageous to a Vector Space Model (VSM) for text classification.
    • 具有计算机可执行指令和设备的计算机可读介质将文档或语料库分类。 张量空间模型(TSM),其通过高阶张量对文本进行建模,表示文档或文档语料库。 由多线代数技术支持,TSM为多因素结构分析提供了框架。 TSM还受到操作和提出的工具的支持,如高阶奇异值分解(HOSVD),用于降低高阶张量的尺寸。 将尺寸减小的张量与表示可能类别的张量进行比较。 因此,文档或文档的语料库选择一个类别。 20个新闻组的数据集的实验结果表明,TSM对于文本分类的向量空间模型(VSM)是有利的。
    • 5. 发明授权
    • Determination of time dependency of search queries
    • 确定搜索查询的时间依赖关系
    • US07693908B2
    • 2010-04-06
    • US11770358
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06F17/30
    • G06F17/30864G06Q30/02
    • 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.
    • 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。
    • 6. 发明授权
    • Forecasting time-independent search queries
    • 预测与时间无关的搜索查询
    • US07685099B2
    • 2010-03-23
    • US11770445
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06F17/30
    • G06F17/30864G06Q30/02
    • 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.
    • 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。
    • 9. 发明申请
    • FORECASTING SEARCH QUERIES BASED ON TIME DEPENDENCIES
    • 根据时间依赖性预测搜索查询
    • US20090006313A1
    • 2009-01-01
    • US11770462
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06F17/40
    • G06Q30/02
    • 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.
    • 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。
    • 10. 发明申请
    • DETERMINATION OF TIME DEPENDENCY OF SEARCH QUERIES
    • 确定搜索查询的时间依赖关系
    • US20090006312A1
    • 2009-01-01
    • US11770358
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06F7/00
    • G06F17/30864G06Q30/02
    • 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.
    • 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。