A similarity measure for text processing

Jung Yi Jiang; Wen Hao Cheng; Yu Shu Chiou; Shie Jue Lee

doi:10.1109/ICMLC.2011.6016998

A similarity measure for text processing

Jung Yi Jiang, Wen Hao Cheng, Yu Shu Chiou, Shie Jue Lee

Department of Computer Science and Information Engineering

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

13 Citations (Scopus)

Abstract

In this paper, we propose a novel similarity measure for document data processing. For two document vectors, the proposed measure takes three cases into account: a) The feature considered appears in both documents, b) the feature considered appears in only one document, and c) the feature considered appears in none of the documents. For the first case, we give a lower bound and decrease the similarity according to the difference between the feature values of the two documents. For the second case, we give a fixed value disregarding the magnitude of the feature value. For the last case, we treat it as an identity, Experimental results show that our proposed method can work more effectively than others.

Original language	English
Title of host publication	Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
Pages	1460-1465
Number of pages	6
DOIs	https://doi.org/10.1109/ICMLC.2011.6016998
Publication status	Published - 2011 Nov 7
Event	2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 - Guilin, Guangxi, China Duration: 2011 Jul 10 → 2011 Jul 13

Publication series

Name	Proceedings - International Conference on Machine Learning and Cybernetics
Volume	4
ISSN (Print)	2160-133X
ISSN (Electronic)	2160-1348

Other

Other	2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
Country/Territory	China
City	Guilin, Guangxi
Period	11-07-10 → 11-07-13

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computational Theory and Mathematics
Computer Networks and Communications
Human-Computer Interaction

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10.1109/ICMLC.2011.6016998

Cite this

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title = "A similarity measure for text processing",

abstract = "In this paper, we propose a novel similarity measure for document data processing. For two document vectors, the proposed measure takes three cases into account: a) The feature considered appears in both documents, b) the feature considered appears in only one document, and c) the feature considered appears in none of the documents. For the first case, we give a lower bound and decrease the similarity according to the difference between the feature values of the two documents. For the second case, we give a fixed value disregarding the magnitude of the feature value. For the last case, we treat it as an identity, Experimental results show that our proposed method can work more effectively than others.",

author = "Jiang, {Jung Yi} and Cheng, {Wen Hao} and Chiou, {Yu Shu} and Lee, {Shie Jue}",

year = "2011",

month = nov,

day = "7",

doi = "10.1109/ICMLC.2011.6016998",

language = "English",

isbn = "9781457703065",

series = "Proceedings - International Conference on Machine Learning and Cybernetics",

pages = "1460--1465",

booktitle = "Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011",

note = "2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 ; Conference date: 10-07-2011 Through 13-07-2011",

}

Jiang, JY, Cheng, WH, Chiou, YS & Lee, SJ 2011, A similarity measure for text processing. in Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011., 6016998, Proceedings - International Conference on Machine Learning and Cybernetics, vol. 4, pp. 1460-1465, 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, Guangxi, China, 11-07-10. https://doi.org/10.1109/ICMLC.2011.6016998

A similarity measure for text processing. / Jiang, Jung Yi; Cheng, Wen Hao; Chiou, Yu Shu et al.
Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011. 2011. p. 1460-1465 6016998 (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 4).

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

TY - GEN

T1 - A similarity measure for text processing

AU - Jiang, Jung Yi

AU - Cheng, Wen Hao

AU - Chiou, Yu Shu

AU - Lee, Shie Jue

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N2 - In this paper, we propose a novel similarity measure for document data processing. For two document vectors, the proposed measure takes three cases into account: a) The feature considered appears in both documents, b) the feature considered appears in only one document, and c) the feature considered appears in none of the documents. For the first case, we give a lower bound and decrease the similarity according to the difference between the feature values of the two documents. For the second case, we give a fixed value disregarding the magnitude of the feature value. For the last case, we treat it as an identity, Experimental results show that our proposed method can work more effectively than others.

AB - In this paper, we propose a novel similarity measure for document data processing. For two document vectors, the proposed measure takes three cases into account: a) The feature considered appears in both documents, b) the feature considered appears in only one document, and c) the feature considered appears in none of the documents. For the first case, we give a lower bound and decrease the similarity according to the difference between the feature values of the two documents. For the second case, we give a fixed value disregarding the magnitude of the feature value. For the last case, we treat it as an identity, Experimental results show that our proposed method can work more effectively than others.

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BT - Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011

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Y2 - 10 July 2011 through 13 July 2011

ER -

A similarity measure for text processing

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