Computing text similarity using Tree Edit Distance

G. Sidorov; H. Gomez-Adorno; I. Markov; D. Pinto; N. Loya

doi:10.1109/NAFIPS-WConSC.2015.7284129

Computing text similarity using Tree Edit Distance

G. Sidorov, H. Gomez-Adorno, I. Markov, D. Pinto, N. Loya

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

Abstract

© 2015 IEEE.In this paper, we propose the application of the Tree Edit Distance (TED) for calculation of similarity between syntactic n-grams for further detection of soft similarity between texts. The computation of text similarity is the basic task for many natural language processing problems, and it is an open research field. Syntactic n-grams are text features for Vector Space Model construction extracted from dependency trees. Soft similarity is application of Vector Space Model taking into account similarity of features. First, we discuss the advantages of the application of the TED to syntactic n-grams. Then, we present a procedure based on the TED and syntactic n-grams for calculating soft similarity between texts.

Original language	English
Title of host publication	2015 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467372473
DOIs	https://doi.org/10.1109/NAFIPS-WConSC.2015.7284129
Publication status	Published - 29 Sept 2015
Externally published	Yes
Event	Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015 - Redmond, United States Duration: 17 Aug 2015 → 19 Aug 2015

Conference

Conference	Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015
Country/Territory	United States
City	Redmond
Period	17/08/15 → 19/08/15

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10.1109/NAFIPS-WConSC.2015.7284129

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@inproceedings{9b30507653ee4dd0ace97cf89ecfcd11,

title = "Computing text similarity using Tree Edit Distance",

abstract = "{\textcopyright} 2015 IEEE.In this paper, we propose the application of the Tree Edit Distance (TED) for calculation of similarity between syntactic n-grams for further detection of soft similarity between texts. The computation of text similarity is the basic task for many natural language processing problems, and it is an open research field. Syntactic n-grams are text features for Vector Space Model construction extracted from dependency trees. Soft similarity is application of Vector Space Model taking into account similarity of features. First, we discuss the advantages of the application of the TED to syntactic n-grams. Then, we present a procedure based on the TED and syntactic n-grams for calculating soft similarity between texts.",

author = "G. Sidorov and H. Gomez-Adorno and I. Markov and D. Pinto and N. Loya",

year = "2015",

month = sep,

day = "29",

doi = "10.1109/NAFIPS-WConSC.2015.7284129",

language = "English",

booktitle = "2015 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015 ; Conference date: 17-08-2015 Through 19-08-2015",

}

Sidorov, G, Gomez-Adorno, H, Markov, I, Pinto, D & Loya, N 2015, Computing text similarity using Tree Edit Distance. in 2015 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015. Institute of Electrical and Electronics Engineers Inc., Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015, Redmond, United States, 17/08/15. https://doi.org/10.1109/NAFIPS-WConSC.2015.7284129

Computing text similarity using Tree Edit Distance. / Sidorov, G.; Gomez-Adorno, H.; Markov, I. et al.
2015 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015. Institute of Electrical and Electronics Engineers Inc., 2015.

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

TY - GEN

T1 - Computing text similarity using Tree Edit Distance

AU - Sidorov, G.

AU - Gomez-Adorno, H.

AU - Markov, I.

AU - Pinto, D.

AU - Loya, N.

PY - 2015/9/29

Y1 - 2015/9/29

N2 - © 2015 IEEE.In this paper, we propose the application of the Tree Edit Distance (TED) for calculation of similarity between syntactic n-grams for further detection of soft similarity between texts. The computation of text similarity is the basic task for many natural language processing problems, and it is an open research field. Syntactic n-grams are text features for Vector Space Model construction extracted from dependency trees. Soft similarity is application of Vector Space Model taking into account similarity of features. First, we discuss the advantages of the application of the TED to syntactic n-grams. Then, we present a procedure based on the TED and syntactic n-grams for calculating soft similarity between texts.

AB - © 2015 IEEE.In this paper, we propose the application of the Tree Edit Distance (TED) for calculation of similarity between syntactic n-grams for further detection of soft similarity between texts. The computation of text similarity is the basic task for many natural language processing problems, and it is an open research field. Syntactic n-grams are text features for Vector Space Model construction extracted from dependency trees. Soft similarity is application of Vector Space Model taking into account similarity of features. First, we discuss the advantages of the application of the TED to syntactic n-grams. Then, we present a procedure based on the TED and syntactic n-grams for calculating soft similarity between texts.

UR - https://www.scopus.com/pages/publications/84961888075

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U2 - 10.1109/NAFIPS-WConSC.2015.7284129

DO - 10.1109/NAFIPS-WConSC.2015.7284129

M3 - Conference contribution

BT - 2015 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015

Y2 - 17 August 2015 through 19 August 2015

ER -

Computing text similarity using Tree Edit Distance

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