A TOURISM RECOMMENDER SYSTEM BASED ON COLLABORATION AND TEXT ANALYSIS

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Abstract:

This work presents a recommender system that helps travel agents in discovering options for customers, especially those who do not know where to go and what to do. The system analyzes textual messages exchanged between a travel agent and a customer through a private Web chat. Text mining techniques help discover interesting areas in the messages. After that, the system searches a database and retrieves tourist options (like cities and attractions) classified in these interesting areas. The system makes use of a tourism ontology, containing themes and a controlled vocabulary, to identify themes in the textual messages. The system acts as a decision support system, because it does not make recommendations directly to the customer.

Keywords: Collaboration; Decision support systems; Recommender systems; Text mining; Tourism

Document Type: Research Article

DOI: http://dx.doi.org/10.3727/1098305031436980

Affiliations: 1: *Catholic University of Pelotas (UCPEL), R. Félix da Cunha, 412–Pelotas, RS Brazil, 96010-000 2: \dag\Lutheran University of Brazil (ULBRA), R. Miguel Tostes, 101–Canoas, RS Brazil, 94420-280

Publication date: January 1, 2003

More about this publication?
  • Information Technology & Tourism is the first scientific journal dealing with the exciting relationship between information technology and tourism. Information and communication systems embedded in a global net have profound influence on the tourism and travel industry. Reservation systems, distributed multimedia systems, highly mobile working places, electronic markets, and the dominant position of tourism applications in the Internet are noticeable results of this development. And the tourism industry poses several challenges to the IT field and its methodologies.
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