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Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures
- IN WORKSHOP ON WORDNET AND OTHER LEXICAL RESOURCES, SECOND MEETING OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS
, 2001
"... Five different proposed measures of similarity or semantic distance in WordNet were experimentally compared by examining their performance in a real-word spelling correction system. It was found that Jiang and Conrath 's measure gave the best results overall. That of Hirst and St-Onge seriously ..."
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Cited by 338 (4 self)
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Five different proposed measures of similarity or semantic distance in WordNet were experimentally compared by examining their performance in a real-word spelling correction system. It was found that Jiang and Conrath 's measure gave the best results overall. That of Hirst and St
Semantic Distance In Conceptual Graphs
, 1992
"... A modification of Sowa's metric on conceptual graphs is proposed and defended. The metric is computed by locating the least subtype which subsumes the two given types, and adding the distance from each given type to the subsuming type. Implementations using this metric are described, the releva ..."
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Cited by 12 (0 self)
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, the relevance of it to fuzzy problems is explained. 1. Proposed Metric Given two concepts C1 and C2 with types T1 and T2, Garner and Tsui (1987) have proposed a modification of Sowa's semantic distance between C1 and C2 as follows. Find the concept C3 which generalizes C1 and C2 with type T3 such that T3
Test Case Selection for Evaluating Measures of Semantic Distance
- Paper presented at the XXVIII Annual Conference of the Cognitive Science Society
, 2006
"... With a growing number of measures of semantic distance ..."
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Cited by 2 (2 self)
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With a growing number of measures of semantic distance
Semantic similarity based on corpus statistics and lexical taxonomy
- Proc of 10th International Conference on Research in Computational Linguistics, ROCLING’97
, 1997
"... This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantifie ..."
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Cited by 873 (0 self)
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This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better
Measuring Semantic Distance using Distributional Profiles of Concepts
, 2008
"... Semantic distance is a measure of how close or distant in meaning two units of language are. A large number of important natural language problems, including machine translation and word sense disambiguation, can be viewed as semantic distance problems. The two dominant approaches to estimating sema ..."
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Cited by 10 (2 self)
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Semantic distance is a measure of how close or distant in meaning two units of language are. A large number of important natural language problems, including machine translation and word sense disambiguation, can be viewed as semantic distance problems. The two dominant approaches to estimating
Semantic distances for technology landscape visualization
, 2008
"... For more information, please visit our website at ..."
Distributional Measures of Semantic Distance: A Survey
, 2012
"... The ability to mimic human notions of semantic distance has widespread applications. Some measures rely only on raw text (distributional measures) and some rely on knowledge sources such as WordNet. Although extensive studies have been performed to compare WordNet-based measures with human judgment, ..."
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Cited by 4 (1 self)
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The ability to mimic human notions of semantic distance has widespread applications. Some measures rely only on raw text (distributional measures) and some rely on knowledge sources such as WordNet. Although extensive studies have been performed to compare WordNet-based measures with human judgment
A Graph-Theoretic Framework for Semantic Distance
"... Many NLP applications entail that texts are classified based on their semantic distance (how similar or different the texts are). For example, comparing the text of a new document to those of documents of known topics can help identify the topic of the new text. Typically, a distributional distance ..."
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Cited by 3 (0 self)
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Many NLP applications entail that texts are classified based on their semantic distance (how similar or different the texts are). For example, comparing the text of a new document to those of documents of known topics can help identify the topic of the new text. Typically, a distributional distance
Distributional Measures as Proxies for Semantic Distance: A Survey
"... The ability to mimic human notions of semantic distance has widespread applications. Some measures rely only on raw text (distributional measures) and some rely on knowledge sources such as WordNet. Although extensive studies have been performed to compare WordNet-based measures with human judgment, ..."
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Cited by 2 (0 self)
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The ability to mimic human notions of semantic distance has widespread applications. Some measures rely only on raw text (distributional measures) and some rely on knowledge sources such as WordNet. Although extensive studies have been performed to compare WordNet-based measures with human judgment
Matching Algorithm of Web Services Based on Semantic Distance
"... Abstract—With the growing number of web services,the importance of matching and discovery web services is increasing. Using domain ontology to describe the semantic of web services and matching the web services on the semantic level is a hot research pot. In this paper, the problem of matching web s ..."
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Cited by 1 (0 self)
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services is transformed to the computation of semantic similarity between concepts in domain ontology. We propose the semantic similarity can be measured from the semantic distance and consider the factors of pathlengh, depth, local density and numberofdowndir-ection in the algorithm. We establish
Results 1 - 10
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