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Cited by 2,047

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language

Open access
Resnik, P.·1999·Journal of Artificial Intelligence Research

Abstract

This article presents a measure of semantic similarity in an IS-A taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.

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Metadata

Authors
Resnik, P.
Venue
Journal of Artificial Intelligence Research
Published
1999-07-01
Volume
11
Pages
95-130
ISSN
1076-9757 (ISSN-L)
OpenAlex
W1659833910
Cited by
2,047
References
4
FWCI
18.31
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language. https://app.cochat.ai/papers/10.1613/jair.514
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Resnik, P. (1999). Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language. Journal of Artificial Intelligence Research. https://doi.org/10.1613/jair.514

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.