Integrating information extraction agents into a tourism recommender system

Sergio Esparcia; Victor Sanchez-Anguix; Estefania Argente; Ana Garcia-Fornes; Vicente Julian

doi:10.1007/978-3-642-13803-4_24

Integrating information extraction agents into a tourism recommender system

Sergio Esparcia, Victor Sanchez-Anguix, Estefania Argente, Ana Garcia-Fornes, Vicente Julian

Polytechnic University of Valencia

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

13 Citations (Scopus)

Abstract

Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

Original language	English
Title of host publication	Hybrid Artificial Intelligence Systems
Editors	Emilio Corchado, Manuel Graña Romay, Alexandre Manhaes Savio
Place of Publication	Berlin
Publisher	Springer Verlag
Pages	193-200
Number of pages	8
ISBN (Electronic)	978-3-642-13803-4
ISBN (Print)	978-3-642-13802-7
DOIs	https://doi.org/10.1007/978-3-642-13803-4_24
Publication status	Published - 2010

Bibliographical note

Core Rank C by the Australian Government's Excellence in Research project (ERA)

Keywords

recommender systems
information agents

Access to Document

10.1007/978-3-642-13803-4_24

Cite this

Integrating information extraction agents into a tourism recommender system. / Esparcia, Sergio; Sanchez-Anguix, Victor; Argente, Estefania et al.
Hybrid Artificial Intelligence Systems. ed. / Emilio Corchado; Manuel Graña Romay; Alexandre Manhaes Savio. Berlin: Springer Verlag, 2010. p. 193-200.

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

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abstract = "Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.",

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AU - Esparcia, Sergio

AU - Sanchez-Anguix, Victor

AU - Argente, Estefania

AU - Garcia-Fornes, Ana

AU - Julian, Vicente

N1 - Core Rank C by the Australian Government's Excellence in Research project (ERA)

PY - 2010

Y1 - 2010

N2 - Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

AB - Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

KW - recommender systems

KW - information agents

U2 - 10.1007/978-3-642-13803-4_24

DO - 10.1007/978-3-642-13803-4_24

M3 - Conference proceeding

SN - 978-3-642-13802-7

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EP - 200

BT - Hybrid Artificial Intelligence Systems

A2 - Corchado, Emilio

A2 - Graña Romay, Manuel

A2 - Manhaes Savio, Alexandre

PB - Springer Verlag

CY - Berlin

ER -

Integrating information extraction agents into a tourism recommender system

Abstract

Bibliographical note

Keywords

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