Paper: An Active Learning Approach to Finding Related Terms

ACL ID P10-2068
Title An Active Learning Approach to Finding Related Terms
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2010
Authors

We present a novel system that helps non- experts find sets of similar words. The userbeginsbyspecifyingoneormoreseed words. The system then iteratively sug- gests a series of candidate words, which the user can either accept or reject. Cur- renttechniquesforthistasktypicallyboot- strap a classifier based on a fixed seed set. In contrast, our system involves the user throughout the labeling process, using active learning to intelligently ex- plore the space of similar words. In particular, our system can take advan- tage of negative examples provided by the user. Our system combines multiple pre- existing sources of similarity data (a stan- dard thesaurus, WordNet, contextual sim- ilarity), enabling it to capture many types of similarity groups (“synonyms of crash,” “types of car,”...