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INFERRING TOPICS WITH ENTITY LINKING AND ONTOLOGICAL DATA

机译:通过实体链接和本体数据推断主题

摘要

Systems and methods are disclosed for inferring topics from a file containing both audio and video, for example a multimodal or multimedia file, in order to facilitate video indexing. A set of entities is extracted from the file and linked to produce a graph, and reference information is also obtained for the set of entities. Entities may be drawn, for example, from Wikipedia categories, or other large ontological data sources. Analysis of the graph, using unsupervised learning, permits determining clusters in the graph. Extracting features from the clusters, possibly using supervised learning, provides for selection of topic identifiers. The topic identifiers are then used for indexing the file.
机译:公开了用于从包含音频和视频两者的文件(例如,多模式或多媒体文件)中推断主题以便促进视频索引的系统和方法。从文件中提取一组实体并将其链接以生成图形,并且还获得了该实体组的参考信息。例如,可以从Wikipedia类别或其他大型本体数据源中提取实体。使用无监督学习对图形进行分析,可以确定图形中的聚类。从集群中提取特征(可能使用监督学习)可以选择主题标识符。主题标识符然后用于索引文件。

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