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SEGMENTING TOPICAL DISCUSSION THEMES FROM USER-GENERATED POSTS

机译:从用户生成的帖子中细分热门话题

摘要

Techniques are provided for detecting new topics and themes and assigning new posts to existing topic and/or theme clusters in online community discussions. A post posted to an online community is received and a post feature vector representative of the post is created. The post is compared to a plurality of centroid feature vectors, each centroid feature vector being representative of a respective post cluster and associated with a theme. Upon determining that similarity between the post feature vector and one of a plurality of centroid feature vectors satisfies a minimum similarity threshold, the post is assigned to the post cluster of which the centroid feature vector is representative. Upon determining that similarity between the post feature vector and any of the plurality of centroid feature vectors is below the minimum similarity threshold, a new theme cluster is created and the post is assigned to the new theme cluster.
机译:提供了用于检测新主题和主题并将新帖子分配给在线社区讨论中的现有主题和/或主题集群的技术。接收发布到在线社区的帖子,并创建代表该帖子的帖子特征向量。将帖子与多个质心特征向量进行比较,每个质心特征向量代表相应的帖子簇并与主题相关联。在确定后特征向量和多个质心特征向量之一之间的相似度满足最小相似性阈值时,将后征分配给以质心特征向量代表的后簇。在确定后特征向量与多个质心特征向量中的任何一个之间的相似度低于最小相似度阈值时,创建新的主题簇并将后缀分配给新的主题簇。

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