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A Package Recommendation Framework for Trip Planning Activities

Abstract : Classical recommender systems provide users with ranked lists of recommendations, where each one consists of a single item. However, these ranked lists are not suitable for applications such as trip planning, which deal with heterogeneous items. In this paper, we focus on the problem of recommending a set of packages to the user, where each package is constituted with a set of different Points of Interest that may constitute a tour. Given a collection of POIs, our goal is to recommend the most interesting packages for the user, where each package satisfies the budget constraints. We formally define the problem and we present a novel composite recommendation system, inspired from composite retrieval. Experimental evaluation of our proposed system, using a real-world dataset demonstrates its quality and its ability to improve both diversity and relevance of recommendations.
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https://hal.inria.fr/hal-01404716
Contributor : Idir Benouaret <>
Submitted on : Tuesday, November 29, 2016 - 10:49:20 AM
Last modification on : Tuesday, January 15, 2019 - 5:26:06 PM

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Idir Benouaret, Dominique Lenne. A Package Recommendation Framework for Trip Planning Activities. 10th ACM Conference on Recommender Systems (RECSYS16), Sep 2016, Boston, United States. pp.203-206, ⟨10.1145/2959100.2959183⟩. ⟨hal-01404716⟩

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