会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 3. 发明授权
    • Identification of similar queries based on overall and partial similarity of time series
    • 基于时间序列的总体和部分相似性识别类似查询
    • US08290921B2
    • 2012-10-16
    • US11770505
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06F7/00G06F17/30
    • G06F17/30864G06F17/3064
    • Techniques for identifying similar queries based on their overall similarity and partial similarity of time series of frequencies of the queries are provided. To identify queries that are similar to a target query, the query analysis system generates, for each query, an overall similarity score for that query and the target query based on the time series of the query and the target query. The query analysis system also generates, for each query, partial similarity scores for the query and the target query based on various time sub-series of the overall time series of the queries. The query analysis system then identifies queries as being similar to the target query based on the overall similarity scores and the partial similarity scores of the queries.
    • 提供了基于其查询的时间序列的总体相似性和部分相似性来识别类似查询的技术。 为了识别类似于目标查询的查询,查询分析系统根据查询和目标查询的时间序列为每个查询生成该查询和目标查询的总体相似性得分。 查询分析系统还根据查询的整个时间序列的各种时间子序列,为每个查询生成查询和目标查询的部分相似度分数。 然后,查询分析系统基于查询的总体相似性得分和部分相似性得分将查询识别为与目标查询相似。
    • 4. 发明申请
    • PREDICTION OF FUTURE POPULARITY OF QUERY TERMS
    • 预测未来的QUERY条款的普遍性
    • US20090222321A1
    • 2009-09-03
    • US12147468
    • 2008-06-26
    • Ning LiuJun YanZheng ChenJian Wang
    • Ning LiuJun YanZheng ChenJian Wang
    • G06F17/30
    • G06Q30/0202G06F16/951G06F2216/03
    • Disclosed is a system and method that allows a computer system the ability to predict what query terms in a search will be popular. The system creates a unified model that determines the future popularity of a query term over a period of time in the future. The unified model averages the results of three different prediction models to obtain a prediction of the future popularity of a query term. The prediction from the unified model is compared against a threshold value of popularity over a time period. When the predicted popularity of the query exceeds the threshold the term is stored. In some embodiments the period that the term exceeds the threshold may also be stored.
    • 公开了一种系统和方法,其允许计算机系统预测搜索中的哪些查询术语将是流行的能力。 该系统创建一个统一的模型,确定未来一段时间内查询词的未来流行度。 统一模型对三种不同预测模型的结果进行平均,以获得对查询词的未来流行度的预测。 将统一模型的预测与一段时间内的人气阈值进行比较。 当查询的预测流行度超过阈值时,该项被存储。 在一些实施例中,术语超过阈值的周期也可以被存储。
    • 6. 发明授权
    • Forecasting search queries based on time dependencies
    • 基于时间依赖性预测搜索查询
    • US07685100B2
    • 2010-03-23
    • US11770462
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06F17/30
    • 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。
    • 7. 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。
    • 8. 发明申请
    • IDENTIFICATION OF EVENTS OF SEARCH QUERIES
    • 识别搜索查询的事件
    • US20090006294A1
    • 2009-01-01
    • US11770423
    • 2007-06-28
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • Ning LiuJun YanBenyu ZhangZheng ChenJian Wang
    • G06N5/00
    • 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。
    • 9. 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。
    • 10. 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。