Using emotion to diversify document rankings

Yashar Moshfeghi; Guido Zuccon; Joemon M. Jose

doi:10.1007/978-3-642-23318-0_34

Using emotion to diversify document rankings

Yashar Moshfeghi, Guido Zuccon, Joemon M. Jose

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

Abstract

The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two approaches are proposed to consider emotion features for diversification, and they are empirically tested on the TREC 678 Interactive Track collection. The results show that emotion features are capable of enhancing retrieval effectiveness.

Original language	English
Title of host publication	Advances in Information Retrieval Theory
Subtitle of host publication	Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011. Proceedings
Editors	Giambattista Amati, Fabio Crestani
Place of Publication	Berlin
Publisher	Springer
Pages	337-341
Number of pages	5
ISBN (Print)	9783642233173, 9783642233180
DOIs	https://doi.org/10.1007/978-3-642-23318-0_34
Publication status	Published - 1 Sept 2011
Event	Third International Conference on the Theory of Information Retrieval - Bertinoro, Italy Duration: 12 Sept 2011 → 14 Sept 2011

Conference

Conference	Third International Conference on the Theory of Information Retrieval
Abbreviated title	ICTIR 2011
Country/Territory	Italy
City	Bertinoro
Period	12/09/11 → 14/09/11

Keywords

emotion
information retrieval systems
diversification
retrieval effectiveness

Access to Document

10.1007/978-3-642-23318-0_34

Cite this

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title = "Using emotion to diversify document rankings",

abstract = "The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two approaches are proposed to consider emotion features for diversification, and they are empirically tested on the TREC 678 Interactive Track collection. The results show that emotion features are capable of enhancing retrieval effectiveness.",

keywords = "emotion, information retrieval systems, diversification, retrieval effectiveness",

author = "Yashar Moshfeghi and Guido Zuccon and Jose, \{Joemon M.\}",

year = "2011",

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doi = "10.1007/978-3-642-23318-0\_34",

language = "English",

isbn = "9783642233173",

pages = "337--341",

editor = "Giambattista Amati and Fabio Crestani",

booktitle = "Advances in Information Retrieval Theory",

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note = "Third International Conference on the Theory of Information Retrieval, ICTIR 2011 ; Conference date: 12-09-2011 Through 14-09-2011",

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Moshfeghi, Y, Zuccon, G & Jose, JM 2011, Using emotion to diversify document rankings. in G Amati & F Crestani (eds), Advances in Information Retrieval Theory: Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011. Proceedings. Springer, Berlin, pp. 337-341, Third International Conference on the Theory of Information Retrieval, Bertinoro, Italy, 12/09/11. https://doi.org/10.1007/978-3-642-23318-0_34

Using emotion to diversify document rankings. / Moshfeghi, Yashar; Zuccon, Guido; Jose, Joemon M.
Advances in Information Retrieval Theory: Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011. Proceedings. ed. / Giambattista Amati; Fabio Crestani. Berlin: Springer, 2011. p. 337-341.

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

TY - GEN

T1 - Using emotion to diversify document rankings

AU - Moshfeghi, Yashar

AU - Zuccon, Guido

AU - Jose, Joemon M.

PY - 2011/9/1

Y1 - 2011/9/1

N2 - The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two approaches are proposed to consider emotion features for diversification, and they are empirically tested on the TREC 678 Interactive Track collection. The results show that emotion features are capable of enhancing retrieval effectiveness.

AB - The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two approaches are proposed to consider emotion features for diversification, and they are empirically tested on the TREC 678 Interactive Track collection. The results show that emotion features are capable of enhancing retrieval effectiveness.

KW - emotion

KW - information retrieval systems

KW - diversification

KW - retrieval effectiveness

U2 - 10.1007/978-3-642-23318-0_34

DO - 10.1007/978-3-642-23318-0_34

M3 - Conference contribution book

SN - 9783642233173

SN - 9783642233180

SP - 337

EP - 341

BT - Advances in Information Retrieval Theory

A2 - Amati, Giambattista

A2 - Crestani, Fabio

PB - Springer

CY - Berlin

T2 - Third International Conference on the Theory of Information Retrieval

Y2 - 12 September 2011 through 14 September 2011

ER -

Using emotion to diversify document rankings

Abstract

Conference

Keywords

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