Contextual correlates of synonymy
Communications of the ACM
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Question answering with lexical chains propagating verb arguments
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Identifying semantic relations and functional properties of human verb associations
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Modeling adjectives in computational relational lexica
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Automatically creating datasets for measures of semantic relatedness
LD '06 Proceedings of the Workshop on Linguistic Distances
Using the structure of a conceptual network in computing semantic relatedness
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Social Semantics and Its Evaluation by Means of Semantic Relatedness and Open Topic Models
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
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Various semantic relatedness, similarity, and distance measures have been proposed in the past decade and many NLP-applications strongly rely on these semantic measures. Researchers compete for better algorithms and normally only few percentage points seem to suffice in order to prove a new measure outperforms an older one. In this paper we present a meta-study comparing various semantic measures and their correlation with human judgments. We show that the results are rather inconsistent and ask for detailed analyses as well as clarification. We argue that the definition of a shared task might bring us considerably closer to understanding the concept of semantic relatedness.