Difference between revisions of "WordSimilarity-353 Test Collection (State of the art)"
Jump to navigation
Jump to search
Line 20: | Line 20: | ||
== Table of results == | == Table of results == | ||
+ | |||
+ | * '''Listed in order of increasing Spearman's rho.''' | ||
{| border="1" cellpadding="5" cellspacing="1" | {| border="1" cellpadding="5" cellspacing="1" | ||
Line 31: | Line 33: | ||
| 0.646 | | 0.646 | ||
|} | |} | ||
− | |||
== References == | == References == |
Revision as of 12:41, 3 October 2013
- WordSimilarity-353 Test Collection
- contains two sets of English word pairs along with human-assigned similarity judgements
- first set (set1) contains 153 word pairs along with their similarity scores assigned by 13 subjects
- second set (set2) contains 200 word pairs with similarity assessed by 16 subjects
- WordSimilarity-353 dataset is available here
- performance is measured by Spearman's rank correlation coefficient
- introduced by Finkelstein et al. (2002)
- subsequently used by many other researchers
0.75 Spearman rank correlation
http://www.cs.technion.ac.il/~gabr/papers/ijcai-2007-sim.pdf
0.65 Spearman rank correlation http://nlp.stanford.edu/~lmthang/data/papers/conll13_morpho.pdf
Table of results
- Listed in order of increasing Spearman's rho.
Algorithm | Reference | Spearman's rho |
---|---|---|
HSMN+csmRNN | Luong et al. (2013) | 0.646 |
References
Luong, Minh-Thang, Richard Socher, and Christopher D. Manning. (2013) Better word representations with recursive neural networks for morphology. CoNLL-2013: 104.