SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees

Marco Antonio Sobrevilla-Cabezudo; Arturo Oncevay-Marcos; Andrés Melgar

doi:10.1007/978-3-319-77113-7_15

SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees

Marco Antonio Sobrevilla-Cabezudo, Arturo Oncevay-Marcos, Andrés Melgar

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

1 Scopus citations

Abstract

Word Sense Disambiguation (WSD) is the field that seeks to determine the correct sense of a word in a given context. In this paper, we present a WSD method based on random walks over a dependency tree, whose nodes are word-senses from the WordNet. Besides, our method incorporates prior knowledge about the frequency of use of the word-senses. We observed that our results outperform several graph-based WSD methods in All-Word task of SensEval-2 and SensEval-3, including the baseline, where the nouns and verbs part-of-speech show the better improvement in their F-measure scores.

Original language	English
Title of host publication	Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers
Editors	Alexander Gelbukh
Publisher	Springer Verlag
Pages	185-194
Number of pages	10
ISBN (Print)	9783319771120
DOIs	https://doi.org/10.1007/978-3-319-77113-7_15
State	Published - 2018
Event	18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017 - Budapest, Hungary Duration: 17 Apr 2017 → 23 Apr 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10761 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017
Country/Territory	Hungary
City	Budapest
Period	17/04/17 → 23/04/17

Keywords

Dependency tree
Random walks
Word Sense Disambiguation

Access to Document

10.1007/978-3-319-77113-7_15

Cite this

Sobrevilla-Cabezudo, M. A., Oncevay-Marcos, A., & Melgar, A. (2018). SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees. In A. Gelbukh (Ed.), Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers (pp. 185-194). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10761 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-77113-7_15

Sobrevilla-Cabezudo, Marco Antonio ; Oncevay-Marcos, Arturo ; Melgar, Andrés. / SenseDependency-rank : A word sense disambiguation method based on random walks and dependency trees. Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers. editor / Alexander Gelbukh. Springer Verlag, 2018. pp. 185-194 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8f1a461e92764f9697a092c227c11191,

title = "SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees",

abstract = "Word Sense Disambiguation (WSD) is the field that seeks to determine the correct sense of a word in a given context. In this paper, we present a WSD method based on random walks over a dependency tree, whose nodes are word-senses from the WordNet. Besides, our method incorporates prior knowledge about the frequency of use of the word-senses. We observed that our results outperform several graph-based WSD methods in All-Word task of SensEval-2 and SensEval-3, including the baseline, where the nouns and verbs part-of-speech show the better improvement in their F-measure scores.",

keywords = "Dependency tree, Random walks, Word Sense Disambiguation",

author = "Sobrevilla-Cabezudo, {Marco Antonio} and Arturo Oncevay-Marcos and Andr{\'e}s Melgar",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017 ; Conference date: 17-04-2017 Through 23-04-2017",

year = "2018",

doi = "10.1007/978-3-319-77113-7_15",

language = "English",

isbn = "9783319771120",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "185--194",

editor = "Alexander Gelbukh",

booktitle = "Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers",

}

Sobrevilla-Cabezudo, MA, Oncevay-Marcos, A & Melgar, A 2018, SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees. in A Gelbukh (ed.), Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10761 LNCS, Springer Verlag, pp. 185-194, 18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017, Budapest, Hungary, 17/04/17. https://doi.org/10.1007/978-3-319-77113-7_15

SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees. / Sobrevilla-Cabezudo, Marco Antonio; Oncevay-Marcos, Arturo; Melgar, Andrés.
Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers. ed. / Alexander Gelbukh. Springer Verlag, 2018. p. 185-194 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10761 LNCS).

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

TY - GEN

T1 - SenseDependency-rank

T2 - 18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017

AU - Sobrevilla-Cabezudo, Marco Antonio

AU - Oncevay-Marcos, Arturo

AU - Melgar, Andrés

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - Word Sense Disambiguation (WSD) is the field that seeks to determine the correct sense of a word in a given context. In this paper, we present a WSD method based on random walks over a dependency tree, whose nodes are word-senses from the WordNet. Besides, our method incorporates prior knowledge about the frequency of use of the word-senses. We observed that our results outperform several graph-based WSD methods in All-Word task of SensEval-2 and SensEval-3, including the baseline, where the nouns and verbs part-of-speech show the better improvement in their F-measure scores.

AB - Word Sense Disambiguation (WSD) is the field that seeks to determine the correct sense of a word in a given context. In this paper, we present a WSD method based on random walks over a dependency tree, whose nodes are word-senses from the WordNet. Besides, our method incorporates prior knowledge about the frequency of use of the word-senses. We observed that our results outperform several graph-based WSD methods in All-Word task of SensEval-2 and SensEval-3, including the baseline, where the nouns and verbs part-of-speech show the better improvement in their F-measure scores.

KW - Dependency tree

KW - Random walks

KW - Word Sense Disambiguation

UR - http://www.scopus.com/inward/record.url?scp=85055427090&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-77113-7_15

DO - 10.1007/978-3-319-77113-7_15

M3 - Conference contribution

AN - SCOPUS:85055427090

SN - 9783319771120

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 185

EP - 194

BT - Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers

A2 - Gelbukh, Alexander

PB - Springer Verlag

Y2 - 17 April 2017 through 23 April 2017

ER -

Sobrevilla-Cabezudo MA, Oncevay-Marcos A, Melgar A. SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees. In Gelbukh A, editor, Computational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers. Springer Verlag. 2018. p. 185-194. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-77113-7_15

SenseDependency-rank: A word sense disambiguation method based on random walks and dependency trees

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this