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GRAPH-BASED ACTIVITY DISCOVERY IN HETEROGENEOUS PERSONAL CORPORA

机译:基于图形的异构个人语料库的活动发现

摘要

The present disclosure relates to systems and methods for discovering relatedness between entities from a corpora of information by automatically extracting attributes from the plurality of heterogeneous entities in a graph. A standardized representation of the extracted attributes from the plurality of heterogeneous entities are propagated across the graph and these propagated attributes are used to find a degree to which the plurality of heterogeneous entities are associated with the extracted attributes. The degree to which the plurality of heterogeneous entities are associated with the extracted attributes is used to create a representation space illustrating a level of relatedness of an entity to another entity of the plurality of heterogeneous entities. The representation space may be efficiently updated when updates to the graph are received by determining a delta representation space caused by the update to the graph and creating a new representation space by adding the delta representation space to the representation space.
机译:本公开涉及通过在图表中自动提取来自多个异构实体的信息来从信息中发现实体之间的相关性的系统和方法。从多个异构实体的提取属性的标准化表示在图中传播,并且这些传播的属性用于找到多个异构实体与提取的属性相关联的程度。多个异构实体与提取的属性相关联的程度用于创建表示实体与多个异构实体的另一实体的实体相关性级别的表示空间。当通过确定由图形的更新引起的Δ表示空间并通过将增量表示空间添加到表示空间来创建新的表示空间来接收到图表的更新时,可以有效地更新表示空间。

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