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    • 4. 发明授权
    • System and method for identifying query-relevant keywords in documents with latent semantic analysis
    • 在具有潜在语义分析的文档中识别查询相关关键词的系统和方法
    • US07440947B2
    • 2008-10-21
    • US10987377
    • 2004-11-12
    • John E. AdcockMatthew CooperAndreas GirgensohnLynn D. Wilcox
    • John E. AdcockMatthew CooperAndreas GirgensohnLynn D. Wilcox
    • G06F7/00
    • G06F17/2795G06F17/2785G06F17/30613Y10S707/99933Y10S707/99936Y10S707/99937
    • A system and method for identifying query-related keywords in documents found in a search using latent semantic analysis. The documents are represented as a document term matrix M containing one or more document term-weight vectors d, which may be term-frequency (tf) vectors or term-frequency inverse-document-frequency (tf-idf) vectors. This matrix is subjected to a truncated singular value decomposition. The resulting transform matrix U can be used to project a query term-weight vector q into the reduced N-dimensional space, followed by its expansion back into the full vector space using the inverse of U.To perform a search, the similarity of qexpanded is measured relative to each candidate document vector in this space. Exemplary similarity functions are dot product and cosine similarity. Keywords are selected with the highest values in qexpanded that are also comprised in at least one document. Matching keywords from the query may be highlighted in the search results.
    • 用于使用潜在语义分析在搜索中发现的文档中识别查询相关关键字的系统和方法。 这些文件被表示为包含一个或多个文档术语权重向量d的文档术语矩阵,其可以是术语频率(tf)向量或术语频率逆文档频率(tf) -idf)载体。 该矩阵经受截断的奇异值分解。 所得到的变换矩阵 U可用于将查询项权重向量q投影到缩小的N维空间中,然后使用 U。 为了执行搜索,相对于该空间中的每个候选文档向量测量q expanded 的相似度。 示例性相似度函数是点积和余弦相似度。 关键字被选择,其中也包含在至少一个文档中的q 扩展的最高值。 查询中的匹配关键字可能会在搜索结果中突出显示。
    • 5. 发明申请
    • System and method for identifying query-relevant keywords in documents with latent semantic analysis
    • 在具有潜在语义分析的文档中识别查询相关关键词的系统和方法
    • US20060106767A1
    • 2006-05-18
    • US10987377
    • 2004-11-12
    • John AdcockMatthew CooperAndreas GirgensohnLynn Wilcox
    • John AdcockMatthew CooperAndreas GirgensohnLynn Wilcox
    • G06F17/30
    • G06F17/2795G06F17/2785G06F17/30613Y10S707/99933Y10S707/99936Y10S707/99937
    • A system and method for identifying query-related keywords in documents found in a search using latent semantic analysis. The documents are represented as a document term matrix M containing one or more document term-weight vectors d, which may be term-frequency (tf) vectors or term-frequency inverse-document-frequency (tf-idf) vectors. This matrix is subjected to a truncated singular value decomposition. The resulting transform matrix U can be used to project a query term-weight vector q into the reduced N-dimensional space, followed by its expansion back into the full vector space using the inverse of U. To perform a search, the similarity of qexpanded is measured relative to each candidate document vector in this space. Exemplary similarity functions are dot product and cosine similarity. Keywords are selected with the highest values in qexpanded that are also comprised in at least one document. Matching keywords from the query may be highlighted in the search results.
    • 用于使用潜在语义分析在搜索中发现的文档中识别查询相关关键字的系统和方法。 这些文件被表示为包含一个或多个文档术语权重向量d的文档术语矩阵,其可以是术语频率(tf)向量或术语频率逆文档频率(tf) -idf)载体。 该矩阵经历截断的奇异值分解。 所得到的变换矩阵 U可用于将查询项权重向量q投影到缩小的N维空间中,然后使用 U。 为了执行搜索,相对于该空间中的每个候选文档向量测量q expanded 的相似度。 示例性相似度函数是点积和余弦相似度。 关键字被选择,其中也包含在至少一个文档中的q 扩展的最高值。 查询中的匹配关键字可能会在搜索结果中突出显示。
    • 7. 发明授权
    • Segmenting time based on the geographic distribution of activity in sensor data
    • 基于传感器数据中活动的地理分布的分段时间
    • US08310542B2
    • 2012-11-13
    • US11946794
    • 2007-11-28
    • Andreas GirgensohnFrank M. ShipmanLynn D. Wilcox
    • Andreas GirgensohnFrank M. ShipmanLynn D. Wilcox
    • H04N7/18
    • G08B13/19613G06K9/00771
    • The invention segments detector input according to the time and the level of activity in different geographic regions of a locality. In one embodiment of the invention the detector input is comprised of video stream from one or more cameras to identify activity in the video. In one embodiment of the invention the detector input is comprised of sensor outputs such as RFID, pressure plates, etc. Various embodiments of the invention include identifying boundaries based on the level of activity. In embodiments of the invention, the boundaries can be used to select time dimensions. In one embodiment, by recognizing time dimensions with distinctive activity patterns, systems can better present overviews of activity over time.
    • 本发明根据当地不同地理区域的时间和活动水平来划分检测器输入。 在本发明的一个实施例中,检测器输入由来自一个或多个摄像机的视频流组成,以识别视频中的活动。 在本发明的一个实施例中,检测器输入由诸如RFID,压力板等的传感器输出组成。本发明的各种实施例包括基于活动水平来识别边界。 在本发明的实施例中,边界可用于选择时间维度。 在一个实施例中,通过用特征活动模式识别时间维度,系统可以更好地呈现随时间的活动的概述。
    • 10. 发明授权
    • Methods and interfaces for event timeline and logs of video streams
    • 事件时间线和视频流日志的方法和接口
    • US07996771B2
    • 2011-08-09
    • US11324971
    • 2006-01-03
    • Andreas GirgensohnFrank M. ShipmanLynn Wilcox
    • Andreas GirgensohnFrank M. ShipmanLynn Wilcox
    • G06F3/00
    • G06F17/3079G06F17/30802G06F17/30843G08B13/19682
    • Techniques for generating timelines and event logs from one or more fixed-position cameras based on the identification of activity in the video are presented. Various embodiments of the invention include an assessment of the importance of the activity, the creation of a timeline identifying events of interest, and interaction techniques for seeing more details of an event or alternate views of the video. In one embodiment, motion detection is used to determine activity in one or more synchronized video streams. In another embodiment, events are determined based on periods of activity and assigned importance assessments based on the activity, important locations in the video streams, and events from other sensors. In different embodiments, the interface consists of a timeline, event log, and map.
    • 提出了基于视频中的活动识别从一个或多个固定位置摄像机生成时间线和事件日志的技术。 本发明的各种实施例包括评估活动的重要性,创建识别感兴趣事件的时间线以及用于查看视频的事件或替代视图的更多细节的交互技术。 在一个实施例中,运动检测用于确定一个或多个同步视频流中的活动。 在另一个实施例中,基于活动的周期和基于活动的重要性评估,视频流中的重要位置以及来自其他传感器的事件来确定事件。 在不同的实施例中,接口由时间线,事件日志和地图组成。