Keyword extraction from dialogue sentences using semantic and topical relatedness

Yunseok Noh; Jeong Woo Son; Seong Bae Park

doi:10.1007/978-3-642-42054-2_17

Keyword extraction from dialogue sentences using semantic and topical relatedness

Yunseok Noh, Jeong Woo Son, Seong Bae Park

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

Abstract

Dialogue reflects interests of the participants at that moment. Thus, it is desirable to extract keywords from each dialogue sentence as soon as they are spoken, because the keywords from dialogue can be used for various fields importantly such as personal assistant services, advertisement, and so on. This paper proposes a novel method of keyword extraction from dialogue sentences. The proposed method determines a word as a keyword by using semantic information of words in a dialogue sentence. That is, the proposed method extracts the keywords that are more semantically important within their sentences and more topically related to the dialogue. In the experiments on the ICSI meeting corpus, the proposed method achieves the state-of-the-art performance.

Original language	English
Title of host publication	Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings
Pages	129-136
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-42054-2_17
Publication status	Published - 2013
Event	20th International Conference on Neural Information Processing, ICONIP 2013 - Daegu, Korea, Republic of Duration: 3 Nov 2013 → 7 Nov 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	8226 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th International Conference on Neural Information Processing, ICONIP 2013
Country/Territory	Korea, Republic of
City	Daegu
Period	3/11/13 → 7/11/13

Keywords

Dialogue sentences
Keyword extraction
Semantic relatedness

Access to Document

10.1007/978-3-642-42054-2_17

Cite this

Noh, Y., Son, J. W., & Park, S. B. (2013). Keyword extraction from dialogue sentences using semantic and topical relatedness. In Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings (PART 1 ed., pp. 129-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8226 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-42054-2_17

Noh, Yunseok ; Son, Jeong Woo ; Park, Seong Bae. / Keyword extraction from dialogue sentences using semantic and topical relatedness. Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings. PART 1. ed. 2013. pp. 129-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Keyword extraction from dialogue sentences using semantic and topical relatedness",

abstract = "Dialogue reflects interests of the participants at that moment. Thus, it is desirable to extract keywords from each dialogue sentence as soon as they are spoken, because the keywords from dialogue can be used for various fields importantly such as personal assistant services, advertisement, and so on. This paper proposes a novel method of keyword extraction from dialogue sentences. The proposed method determines a word as a keyword by using semantic information of words in a dialogue sentence. That is, the proposed method extracts the keywords that are more semantically important within their sentences and more topically related to the dialogue. In the experiments on the ICSI meeting corpus, the proposed method achieves the state-of-the-art performance.",

keywords = "Dialogue sentences, Keyword extraction, Semantic relatedness",

author = "Yunseok Noh and Son, {Jeong Woo} and Park, {Seong Bae}",

year = "2013",

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

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booktitle = "Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings",

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note = "20th International Conference on Neural Information Processing, ICONIP 2013 ; Conference date: 03-11-2013 Through 07-11-2013",

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Noh, Y, Son, JW & Park, SB 2013, Keyword extraction from dialogue sentences using semantic and topical relatedness. in Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 8226 LNCS, pp. 129-136, 20th International Conference on Neural Information Processing, ICONIP 2013, Daegu, Korea, Republic of, 3/11/13. https://doi.org/10.1007/978-3-642-42054-2_17

Keyword extraction from dialogue sentences using semantic and topical relatedness. / Noh, Yunseok; Son, Jeong Woo; Park, Seong Bae.
Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings. PART 1. ed. 2013. p. 129-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8226 LNCS, No. PART 1).

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

TY - GEN

T1 - Keyword extraction from dialogue sentences using semantic and topical relatedness

AU - Noh, Yunseok

AU - Son, Jeong Woo

AU - Park, Seong Bae

PY - 2013

Y1 - 2013

N2 - Dialogue reflects interests of the participants at that moment. Thus, it is desirable to extract keywords from each dialogue sentence as soon as they are spoken, because the keywords from dialogue can be used for various fields importantly such as personal assistant services, advertisement, and so on. This paper proposes a novel method of keyword extraction from dialogue sentences. The proposed method determines a word as a keyword by using semantic information of words in a dialogue sentence. That is, the proposed method extracts the keywords that are more semantically important within their sentences and more topically related to the dialogue. In the experiments on the ICSI meeting corpus, the proposed method achieves the state-of-the-art performance.

AB - Dialogue reflects interests of the participants at that moment. Thus, it is desirable to extract keywords from each dialogue sentence as soon as they are spoken, because the keywords from dialogue can be used for various fields importantly such as personal assistant services, advertisement, and so on. This paper proposes a novel method of keyword extraction from dialogue sentences. The proposed method determines a word as a keyword by using semantic information of words in a dialogue sentence. That is, the proposed method extracts the keywords that are more semantically important within their sentences and more topically related to the dialogue. In the experiments on the ICSI meeting corpus, the proposed method achieves the state-of-the-art performance.

KW - Dialogue sentences

KW - Keyword extraction

KW - Semantic relatedness

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U2 - 10.1007/978-3-642-42054-2_17

DO - 10.1007/978-3-642-42054-2_17

M3 - Conference contribution

AN - SCOPUS:84893343408

SN - 9783642420535

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

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EP - 136

BT - Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings

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Noh Y, Son JW, Park SB. Keyword extraction from dialogue sentences using semantic and topical relatedness. In Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings. PART 1 ed. 2013. p. 129-136. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-42054-2_17

Keyword extraction from dialogue sentences using semantic and topical relatedness

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