The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Open accessAbstract
The quantification of lexical semantic relatedness has many applications in NLP, and many different measures have been proposed. We evaluate five of these measures, all of which use WordNet as their central resource, by comparing their performance in detecting and correcting real-word spelling errors. An information-content-based measure proposed by Jiang and Conrath is found superior to those proposed by Hirst and St-Onge, Leacock and Chodorow, Lin, and Resnik. In addition, we explain why distributional similarity is not an adequate proxy for lexical semantic relatedness.
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Cites
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An Information-Theoretic Definition of Similarity
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Using Information Content to Evaluate Semantic Similarity in a Taxonomy
Resnik, P. (1995) · arXiv (Cornell University) · doi:10.48550/arxiv.cmp-lg/9511007 · Cited by 3,193
Verbs semantics and lexical selection
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Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy
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FREQUENCY ANALYSIS OF ENGLISH USAGE: LEXICON AND GRAMMAR
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Statistical Methods for the Social Sciences
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Vector Space Models of Word Meaning and Phrase Meaning: A Survey
Erk, K. (2012) · Language and Linguistics Compass · doi:10.1002/lnco.362 · Cited by 321
Argumentation mining: the detection, classification and structure of arguments in text
Palau, R. M., & Moens, M.-F. (2009) · Proceedings of the 12th International Conference on Artificial Intelligence and Law · doi:10.1145/1568234.1568246 · Cited by 316
What helps where – and why? Semantic relatedness for knowledge transfer
Rohrbach, M., Stark, M., Szarvas, G., Gurevych, I., & Schiele, B. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5540121 · Cited by 273
A Survey of Paraphrasing and Textual Entailment Methods
Androutsopoulos, I., & Malakasiotis, P. (2010) · Journal of Artificial Intelligence Research · doi:10.1613/jair.2985 · Cited by 178
Addressing age-related bias in sentiment analysis,
Diaz, M., Johnson, I., Lazar, A., Piper, A. M., & Gergle, D. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173986 · Cited by 138
Metadata
- Authors
- Budanitsky, A., & Hirst, G.
- Venue
- Computational Linguistics
- Publisher
- MIT Press
- Published
- 2006-03-01
- Volume
- 32
- Issue
- 1
- Pages
- 13-47
- ISSN
- 0891-2017 (ISSN-L)
- 1530-9312
- OpenAlex
- W2136930489
- Cited by
- 1,448
- References
- 45
- FWCI
- 94.91
- Type
- journal article
- Language
- en
- Open access
- bronze
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