Integrating information extraction agents into a tourism recommender system

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

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

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 languageEnglish
Title of host publicationHybrid Artificial Intelligence Systems
EditorsEmilio Corchado, Manuel Graña Romay, Alexandre Manhaes Savio
Place of PublicationBerlin
PublisherSpringer Verlag
Pages193-200
Number of pages8
ISBN (Electronic)978-3-642-13803-4
ISBN (Print)978-3-642-13802-7
DOIs
Publication statusPublished - 2010

Bibliographical note

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

Keywords

  • recommender systems
  • information agents

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  • Cite this

    Esparcia, S., Sanchez-Anguix, V., Argente, E., Garcia-Fornes, A., & Julian, V. (2010). Integrating information extraction agents into a tourism recommender system. In E. Corchado, M. Graña Romay, & A. Manhaes Savio (Eds.), Hybrid Artificial Intelligence Systems (pp. 193-200). Berlin: Springer Verlag. https://doi.org/10.1007/978-3-642-13803-4_24