Name
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. 602%), hypernyms-random (92.3% vs. 65.5%) and co-hyponyms-random (97.3% vs. 81.5%). Our results are competitive with state-of-the-art models. |
Year | Venue | DocType |
|---|---|---|
2016 | THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE | Conference |
Volume | Citations | PageRank |
abs/1603.08705 | 0 | 0.34 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrico Santus | 1 | 12 | 4.04 |
| Alessandro Lenci | 2 | 633 | 61.92 |
| Tin-shing Chiu | 3 | 17 | 3.67 |
| Qin Lu | 4 | 689 | 66.45 |
| Chu-Ren Huang | 5 | 600 | 136.84 |