Watset: Local-global graph clustering with applications in sense and frame induction

Ustalov, Dmitry ; Panchenko, Alexander ; Biemann, Chris ; Ponzetto, Simone Paolo

DOI: https://doi.org/10.1162/coli_a_00354
URL: https://www.mitpressjournals.org/doi/full/10.1162/...
Additional URL: https://arxiv.org/abs/1808.06696
Document Type: Article
Year of publication: 2019
The title of a journal, publication series: Computational Linguistics
Volume: 45
Issue number: 3
Page range: 423-479
Place of publication: Cambridge, MA
Publishing house: MIT Press
ISSN: 0891-2017 , 1530-9312
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject: 004 Computer science, internet
Abstract: 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 that reflects the “ambiguity” of its nodes. 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 be also applied to other networks of linguistic data.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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