CompRec-Trip: A composite recommendation system for travel planning

Authors:
Min Xie;Laks V. S. Lakshmanan;Peter T. Wood
Affiliations:
Department of Computer Science, University of British Columbia, Canada;Department of Computer Science, University of British Columbia, Canada;Department of Computer Science and Information Systems, Birkbeck, University of London, UK
Venue:
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Year:
2011

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Abstract

Classical recommender systems provide users with a list of recommendations where each recommendation consists of a single item, e.g., a book or a DVD. However, applications such as travel planning can benefit from a system capable of recommending packages of items, under a user-specified budget and in the form of sets or sequences. In this context, there is a need for a system that can recommend top-k packages for the user to choose from. In this paper, we propose a novel system, CompRec-Trip, which can automatically generate composite recommendations for travel planning. The system leverages rating information from underlying recommender systems, allows flexible package configuration and incorporates users' cost budgets on both time and money. Furthermore, the proposed CompRec-Trip system has a rich graphical user interface which allows users to customize the returned composite recommendations and take into account external local information.