Contextual correlates of synonymy
Communications of the ACM
Placing search in context: the concept revisited
ACM Transactions on Information Systems (TOIS)
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Scaling distributional similarity to large corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Automatic Evaluation of Information Ordering: Kendall's Tau
Computational Linguistics
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Measuring distributional similarity in context
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
| Hi-index | 0.00 |
This task focuses on evaluating word similarity computation in Chinese. We follow the way of Finkelstein et al. (2002) to select word pairs. Then we organize twenty undergraduates who are major in Chinese linguistics to annotate the data. Each pair is assigned a similarity score by each annotator. We rank the word pairs by the average value of similar scores among the twenty annotators. This data is used as gold standard. Four systems participating in this task return their results. We evaluate their results on gold standard data in term of Kendall's tau value, and the results show three of them have a positive correlation with the rank manually created while the taus' value is very small.