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Title: ROOT13 : spotting hypernyms, co-hyponyms and randoms
Authors: Santus, E
Lenci, A
Chiu, TS
Lu, Q
Huang, CR
Issue Date: 2016
Publisher: AAAI press
Source: 30th AAAI Conference on Artificial Intelligence, AAAI 2016, 2016, p. 4262-4263 How to cite?
Abstract: In this paper, we describe ROOT13, a supervised system for the classification of hypernyms, co-hyponyms and random words. The system relies on a Random Forest algorithm and 13 unsupervised corpus-based features. We evaluate it with a 10-fold cross validation on 9,600 pairs, equally distributed among the three classes and involving several Parts-Of- Speech (i.e. adjectives, nouns and verbs). When all the classes are present, ROOT13 achieves an F1 score of 88.3%, against a baseline of 57.6% (vector cosine). When the classification is binary, ROOT13 achieves the following results: hypernyms-co-hyponyms (93.4% vs. 60.2%), hypernymsrandom (92.3% vs. 65.5%) and co-hyponyms-random (97.3% vs. 81.5%). Our results are competitive with stateof-The-Art models.
Description: 30th AAAI Conference on Artificial Intelligence, AAAI 2016, Phoenix, US, 12-17 February 2016
ISBN: 9781577357605
Appears in Collections:Conference Paper

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