文章基本信息

标题：W atset: Local-Global Graph Clustering with Applications in Sense and Frame Induction
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作者：Dmitry Ustalov ; Alexander Panchenko ; Chris Biemann 等
期刊名称：Computational Linguistics
印刷版ISSN：0891-2017
电子版ISSN：1530-9312
出版年度：2019
卷号：45
期号：3
页码：423-479
DOI：10.1162/coli_a_00354
语种：English
出版社：MIT Press
摘要：We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of domains. This algorithm creates an intermediate representation of the input graph, which reflects the “ambiguity” of its nodes. Then, it uses hard clustering to discover clusters in this “disambiguated” intermediate graph. After outlining the approach and analyzing its computational complexity, we demonstrate that Watset shows competitive results in three applications: unsupervised synset induction from a synonymy graph, unsupervised semantic frame induction from dependency triples, and unsupervised semantic class induction from a distributional thesaurus. Our algorithm is generic and can also be applied to other networks of linguistic data.