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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIX pp 43–66Cite as

A Package-to-Group Recommendation Framework

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Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 11310))

Abstract

Recommender systems are important information filtering techniques that retrieve interesting and personalized items for users based on their profiles and past activities. The goal of most recommender systems is to identify a ranked list of items that are likely to be of interest to users. However, there are several applications such as trip planning, where the items to be selected are not intended for single users but for a group of users, and where the group members are interested in package recommendations as collections of items. Recent research on recommender systems has generalized recommendations to suggest packages of items to single users (Package recommendations), and single items to groups of users (Group recommendations). However, the package-to-group recommendation task has not gained much attention. In this paper, we focus on the task of recommending packages of items to groups of users. This is a task with several real life scenarios, such as recommending a set of Points of Interest packages to tourist groups. We formally define the problem of top-k package-to-group recommendations and propose two models for estimating the preference of a group for a package, incorporating features such as package constraint, user impact and package viability. We design ranking algorithms for finding the top-k package-to-group recommendations and we compare our proposed models with baseline approaches stemming from related works. The experimental evaluation of our proposals, using the Yelp dataset demonstrates that our models find packages of high quality considering important features of package-to-group recommendations.

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Notes

  1. 1.

    https://www.yelp.com/dataset/challenge.

  2. 2.

    https://cran.r-project.org/web/packages/recommenderlab/.

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Author information

Authors and Affiliations

  1. Université Jean Monnet Saint Etienne, Laboratoire Hubert Curien UMR 5516, 18 rue Benoit Lauras, 42000, St-Etienne, France

    Idir Benouaret

  2. Sorbonne universités, Université de Technologie de Compiègne, Heudiasyc – UMR CNRS 7253, Compiègne, France

    Dominique Lenne

Authors
  1. Idir Benouaret
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  2. Dominique Lenne
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Correspondence to Idir Benouaret .

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  2. FAW, University of Linz, Linz, Austria

    Roland Wagner

  3. IUT, University Lyon 1, Villeurbanne Cedex, France

    Djamal Benslimane

  4. University of Milan, Crema, Italy

    Ernesto Damiani

  5. University of Michigan-Dearborn, Dearborn, MI, USA

    William I. Grosky

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Benouaret, I., Lenne, D. (2018). A Package-to-Group Recommendation Framework. In: Hameurlain, A., Wagner, R., Benslimane, D., Damiani, E., Grosky, W. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIX. Lecture Notes in Computer Science(), vol 11310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58415-6_2

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  • DOI: https://doi.org/10.1007/978-3-662-58415-6_2

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