CLUSTERING AGGREGATOR FOR RSS FEEDS
    1.
    发明申请
    CLUSTERING AGGREGATOR FOR RSS FEEDS 有权
    聚合聚合器RSS信息

    公开(公告)号:US20090327320A1

    公开(公告)日:2009-12-31

    申请号:US12146481

    申请日:2008-06-26

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30705

    摘要: A method for merging really simple syndication (RSS) feeds. Stories containing one or more terms may be merged into one or more clusters based on one or more links between the stories. A cluster frequency with which the terms occur in each cluster may be determined. A diameter for each cluster may be determined. A cluster that is most similar to one of the clusters may be determined based on the cluster frequency. The most similar cluster with the one of the clusters may be determined based on each diameter, and each cluster frequency.

    摘要翻译: 一种合并真正简单的联合(RSS)馈送的方法。 包含一个或多个术语的故事可以基于故事之间的一个或多个链接合并成一个或多个集群。 可以确定在每个簇中出现术语的聚类频率。 可以确定每个簇的直径。 可以基于群集频率来确定与簇之一最相似的群集。 可以基于每个直径和每个聚类频率来确定具有一个簇的最相似的簇。

    Clustering aggregator for RSS feeds
    2.
    发明授权
    Clustering aggregator for RSS feeds 有权
    用于RSS源的聚类聚合器

    公开(公告)号:US07958125B2

    公开(公告)日:2011-06-07

    申请号:US12146481

    申请日:2008-06-26

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06F17/30705

    摘要: A method for merging really simple syndication (RSS) feeds. Stories containing one or more terms may be merged into one or more clusters based on one or more links between the stories. A cluster frequency with which the terms occur in each cluster may be determined. A diameter for each cluster may be determined. A cluster that is most similar to one of the clusters may be determined based on the cluster frequency. The most similar cluster with the one of the clusters may be determined based on each diameter, and each cluster frequency.

    摘要翻译: 一种合并真正简单的联合(RSS)馈送的方法。 包含一个或多个术语的故事可以基于故事之间的一个或多个链接合并成一个或多个集群。 可以确定在每个簇中出现术语的聚类频率。 可以确定每个簇的直径。 可以基于群集频率来确定与簇之一最相似的群集。 可以基于每个直径和每个聚类频率来确定具有一个簇的最相似的簇。

    Identification of similar queries based on overall and partial similarity of time series
    3.
    发明授权
    Identification of similar queries based on overall and partial similarity of time series 有权
    基于时间序列的总体和部分相似性识别类似查询

    公开(公告)号:US08290921B2

    公开(公告)日:2012-10-16

    申请号:US11770505

    申请日:2007-06-28

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06F17/30864 G06F17/3064

    摘要: 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.

    摘要翻译: 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。

    PREDICTION OF FUTURE POPULARITY OF QUERY TERMS
    4.
    发明申请
    PREDICTION OF FUTURE POPULARITY OF QUERY TERMS 审中-公开
    预测未来的QUERY条款的普遍性

    公开(公告)号:US20090222321A1

    公开(公告)日:2009-09-03

    申请号:US12147468

    申请日:2008-06-26

    IPC分类号: G06F17/30

    摘要: 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.

    摘要翻译: 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。

    Representing queries and determining similarity based on an ARIMA model
    5.
    发明授权
    Representing queries and determining similarity based on an ARIMA model 失效
    基于ARIMA模型表示查询和确定相似性

    公开(公告)号:US08090709B2

    公开(公告)日:2012-01-03

    申请号:US11770307

    申请日:2007-06-28

    IPC分类号: G06F17/30

    CPC分类号: G06Q30/02

    摘要: Representing queries and determining similarity of queries based on an autoregressive integrated moving average (“ARIMA”) model is provided. A query analysis system represents each query by its ARIMA coefficients. The query analysis system may estimate the frequency information for a desired past or future interval based on frequency information for some initial intervals. The query analysis system may also determine the similarity of a pair of queries based on the similarity of their ARIMA coefficients. The query analysis system may use various metrics, such as a correlation metric, to determine the similarity of the ARIMA coefficients.

    摘要翻译: 提供了基于自回归综合移动平均(“ARIMA”)模型的查询和确定查询的相似性。 查询分析系统通过其ARIMA系数表示每个查询。 查询分析系统可以基于一些初始间隔的频率信息来估计期望的过去或将来间隔的频率信息。 查询分析系统还可以基于它们的ARIMA系数的相似度来确定一对查询的相似性。 查询分析系统可以使用诸如相关度量的各种度量来确定ARIMA系数的相似性。

    Forecasting search queries based on time dependencies
    6.
    发明授权
    Forecasting search queries based on time dependencies 有权
    基于时间依赖性预测搜索查询

    公开(公告)号:US07685100B2

    公开(公告)日:2010-03-23

    申请号:US11770462

    申请日:2007-06-28

    IPC分类号: G06F17/30

    CPC分类号: 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。

    Document characterization using a tensor space model
    7.
    发明授权
    Document characterization using a tensor space model 失效
    文档表征使用张量空间模型

    公开(公告)号:US07529719B2

    公开(公告)日:2009-05-05

    申请号:US11378095

    申请日:2006-03-17

    IPC分类号: G06N5/00

    CPC分类号: G06N5/02 G06F17/30705

    摘要: 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.

    摘要翻译: 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。

    IDENTIFICATION OF EVENTS OF SEARCH QUERIES
    8.
    发明申请
    IDENTIFICATION OF EVENTS OF SEARCH QUERIES 有权
    识别搜索查询的事件

    公开(公告)号:US20090006294A1

    公开(公告)日:2009-01-01

    申请号:US11770423

    申请日:2007-06-28

    IPC分类号: G06N5/00

    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。

    Determination of time dependency of search queries
    9.
    发明授权
    Determination of time dependency of search queries 失效
    确定搜索查询的时间依赖关系

    公开(公告)号:US07693908B2

    公开(公告)日:2010-04-06

    申请号:US11770358

    申请日:2007-06-28

    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。

    Forecasting time-independent search queries
    10.
    发明授权
    Forecasting time-independent search queries 有权
    预测与时间无关的搜索查询

    公开(公告)号:US07685099B2

    公开(公告)日:2010-03-23

    申请号:US11770445

    申请日:2007-06-28

    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。