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ACL
2008

Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy

9 years 3 months ago
Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy
We present a novel framework for the discovery and representation of general semantic relationships that hold between lexical items. We propose that each such relationship can be identified with a cluster of patterns that captures this relationship. We give a fully unsupervised algorithm for pattern cluster discovery, which searches, clusters and merges highfrequency words-based patterns around randomly selected hook words. Pattern clusters can be used to extract instances of the corresponding relationships. To assess the quality of discovered relationships, we use the pattern clusters to automatically generate SAT analogy questions. We also compare to a set of known relationships, achieving very good results in both methods. The evaluation (done in both English and Russian) substantiates the premise that our pattern clusters indeed reflect relationships perceived by humans.
Dmitry Davidov, Ari Rappoport
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ACL
Authors Dmitry Davidov, Ari Rappoport
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