A new hybrid semantic similarity measure based on wordnet

Lingling Meng; Junzhong Gu; Zili Zhou

doi:10.1007/978-3-642-35211-9_93

A new hybrid semantic similarity measure based on wordnet

Lingling Meng
, Junzhong Gu
, Zili Zhou

Faculty of Education

East China Normal University
Qufu Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Semantic similarity between words is a general issue in many applications, such as word sense disambiguation, information extraction, ontology construction and so on. Accurate measurement of semantic similarity between words is crucial. It is necessary to design accurate methods for improving the performance of the bulk of applications relying on it. The paper presents a new hybrid method based on WordNet for measuring word sense similarity. Different from related works, both information content and path have been taken into considerate. We evaluate the new measure on the data set of Rubenstein and Goodenough. Experiments show that the coefficient of our proposed measure with human judgment is 0.8817, which demonstrates that the new measure significantly outperformed than related works.

Original language	English
Title of host publication	Network Computing and Information Security
Subtitle of host publication	Second International Conference, NCIS 2012 Shanghai, China, December 7-9, 2012 Proceedings
Editors	Fu LeeWang, Mo Li, Yuan Luo
Pages	739-744
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-642-35211-9_93
State	Published - 2012
Event	2nd International Conference on Network Computing and Information Security, NCIS 2012 - Shanghai, China Duration: 7 Dec 2012 → 9 Dec 2012

Publication series

Name	Communications in Computer and Information Science
Volume	345
ISSN (Print)	1865-0929

Conference

Conference	2nd International Conference on Network Computing and Information Security, NCIS 2012
Country/Territory	China
City	Shanghai
Period	7/12/12 → 9/12/12

Keywords

WordNet
hybrid measure
information content
semantic similarity

Access to Document

10.1007/978-3-642-35211-9_93

Cite this

Meng, L., Gu, J., & Zhou, Z. (2012). A new hybrid semantic similarity measure based on wordnet. In F. LeeWang, M. Li, & Y. Luo (Eds.), Network Computing and Information Security: Second International Conference, NCIS 2012 Shanghai, China, December 7-9, 2012 Proceedings (pp. 739-744). (Communications in Computer and Information Science; Vol. 345). https://doi.org/10.1007/978-3-642-35211-9_93

@inproceedings{f0d5a39f065b471480644c9a6a4e4dba,

title = "A new hybrid semantic similarity measure based on wordnet",

abstract = "Semantic similarity between words is a general issue in many applications, such as word sense disambiguation, information extraction, ontology construction and so on. Accurate measurement of semantic similarity between words is crucial. It is necessary to design accurate methods for improving the performance of the bulk of applications relying on it. The paper presents a new hybrid method based on WordNet for measuring word sense similarity. Different from related works, both information content and path have been taken into considerate. We evaluate the new measure on the data set of Rubenstein and Goodenough. Experiments show that the coefficient of our proposed measure with human judgment is 0.8817, which demonstrates that the new measure significantly outperformed than related works.",

keywords = "WordNet, hybrid measure, information content, semantic similarity",

author = "Lingling Meng and Junzhong Gu and Zili Zhou",

year = "2012",

doi = "10.1007/978-3-642-35211-9\_93",

language = "英语",

isbn = "9783642352102",

series = "Communications in Computer and Information Science",

pages = "739--744",

editor = "Fu LeeWang and \{ Li\}, Mo and \{ Luo\}, Yuan",

booktitle = "Network Computing and Information Security",

note = "2nd International Conference on Network Computing and Information Security, NCIS 2012 ; Conference date: 07-12-2012 Through 09-12-2012",

}

Meng, L, Gu, J & Zhou, Z 2012, A new hybrid semantic similarity measure based on wordnet. in F LeeWang, M Li & Y Luo (eds), Network Computing and Information Security: Second International Conference, NCIS 2012 Shanghai, China, December 7-9, 2012 Proceedings. Communications in Computer and Information Science, vol. 345, pp. 739-744, 2nd International Conference on Network Computing and Information Security, NCIS 2012, Shanghai, China, 7/12/12. https://doi.org/10.1007/978-3-642-35211-9_93

A new hybrid semantic similarity measure based on wordnet. / Meng, Lingling; Gu, Junzhong; Zhou, Zili.
Network Computing and Information Security: Second International Conference, NCIS 2012 Shanghai, China, December 7-9, 2012 Proceedings. ed. / Fu LeeWang; Mo Li; Yuan Luo. 2012. p. 739-744 (Communications in Computer and Information Science; Vol. 345).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A new hybrid semantic similarity measure based on wordnet

AU - Meng, Lingling

AU - Gu, Junzhong

AU - Zhou, Zili

PY - 2012

Y1 - 2012

N2 - Semantic similarity between words is a general issue in many applications, such as word sense disambiguation, information extraction, ontology construction and so on. Accurate measurement of semantic similarity between words is crucial. It is necessary to design accurate methods for improving the performance of the bulk of applications relying on it. The paper presents a new hybrid method based on WordNet for measuring word sense similarity. Different from related works, both information content and path have been taken into considerate. We evaluate the new measure on the data set of Rubenstein and Goodenough. Experiments show that the coefficient of our proposed measure with human judgment is 0.8817, which demonstrates that the new measure significantly outperformed than related works.

AB - Semantic similarity between words is a general issue in many applications, such as word sense disambiguation, information extraction, ontology construction and so on. Accurate measurement of semantic similarity between words is crucial. It is necessary to design accurate methods for improving the performance of the bulk of applications relying on it. The paper presents a new hybrid method based on WordNet for measuring word sense similarity. Different from related works, both information content and path have been taken into considerate. We evaluate the new measure on the data set of Rubenstein and Goodenough. Experiments show that the coefficient of our proposed measure with human judgment is 0.8817, which demonstrates that the new measure significantly outperformed than related works.

KW - WordNet

KW - hybrid measure

KW - information content

KW - semantic similarity

UR - https://www.scopus.com/pages/publications/84882264229

U2 - 10.1007/978-3-642-35211-9_93

DO - 10.1007/978-3-642-35211-9_93

M3 - 会议稿件

AN - SCOPUS:84882264229

SN - 9783642352102

T3 - Communications in Computer and Information Science

SP - 739

EP - 744

BT - Network Computing and Information Security

A2 - LeeWang, Fu

A2 - Li, Mo

A2 - Luo, Yuan

T2 - 2nd International Conference on Network Computing and Information Security, NCIS 2012

Y2 - 7 December 2012 through 9 December 2012

ER -

A new hybrid semantic similarity measure based on wordnet

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this