Joint Distance and Information Content Word Similarity Measure
Measuring semantic similarity between words is very important to many applications related to information retrieval and natural language processing. In the paper, we have discovered that word similarity metrics suffer from the drawback of obtaining equal similarities of two words, if they have the s...
| Main Authors: | , |
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| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2014
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/8458/ http://ir.unimas.my/id/eprint/8458/1/Joint%20Distance.pdf |
| _version_ | 1848836380758638592 |
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| author | Issa, Atoum Bong, Chih How |
| author_facet | Issa, Atoum Bong, Chih How |
| author_sort | Issa, Atoum |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Measuring semantic similarity between words is very important to many applications related to information retrieval and natural language processing. In the paper, we have discovered that word similarity metrics suffer from the drawback of obtaining equal similarities of two words, if they have the same path and depth values in WordNet. Likewise information content methods which depend on word probability of a corpus tend to posture the same drawback. This paper proposes a new hybrid semantic similarity to overcome the drawbacks by exploiting advantages of Li and Lin methods. On a benchmark set of human judgments on Miller Charles and Rubenstein Goodenough data sets, the proposed approach outperforms existing methods in distance and information content based methods. |
| first_indexed | 2025-11-15T06:22:51Z |
| format | Book Chapter |
| id | unimas-8458 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:22:51Z |
| publishDate | 2014 |
| publisher | Springer Berlin Heidelberg |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-84582022-02-11T07:30:01Z http://ir.unimas.my/id/eprint/8458/ Joint Distance and Information Content Word Similarity Measure Issa, Atoum Bong, Chih How T Technology (General) Measuring semantic similarity between words is very important to many applications related to information retrieval and natural language processing. In the paper, we have discovered that word similarity metrics suffer from the drawback of obtaining equal similarities of two words, if they have the same path and depth values in WordNet. Likewise information content methods which depend on word probability of a corpus tend to posture the same drawback. This paper proposes a new hybrid semantic similarity to overcome the drawbacks by exploiting advantages of Li and Lin methods. On a benchmark set of human judgments on Miller Charles and Rubenstein Goodenough data sets, the proposed approach outperforms existing methods in distance and information content based methods. Springer Berlin Heidelberg 2014 Book Chapter NonPeerReviewed text en http://ir.unimas.my/id/eprint/8458/1/Joint%20Distance.pdf Issa, Atoum and Bong, Chih How (2014) Joint Distance and Information Content Word Similarity Measure. In: Soft Computing Applications and Intelligent Systems. Springer Berlin Heidelberg, pp. 257-267. http://www.researchgate.net/publication/268520347_Joint_Distance_and_Information_Content_Word_Similarity_Measure DOI: 10.1007/978-3-642-40567-9_22 |
| spellingShingle | T Technology (General) Issa, Atoum Bong, Chih How Joint Distance and Information Content Word Similarity Measure |
| title | Joint Distance and Information Content Word Similarity Measure |
| title_full | Joint Distance and Information Content Word Similarity Measure |
| title_fullStr | Joint Distance and Information Content Word Similarity Measure |
| title_full_unstemmed | Joint Distance and Information Content Word Similarity Measure |
| title_short | Joint Distance and Information Content Word Similarity Measure |
| title_sort | joint distance and information content word similarity measure |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/8458/ http://ir.unimas.my/id/eprint/8458/ http://ir.unimas.my/id/eprint/8458/ http://ir.unimas.my/id/eprint/8458/1/Joint%20Distance.pdf |