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Authors: Mouzhi Ge 1 ; Dietmar Jannach 2 ; Fatih Gedikli 2 and Martin Hepp 1

Affiliations: 1 Universität der Bundeswehr Munich, Germany ; 2 Technische Universität Dortmund, Germany

Keyword(s): Recommender System, Evaluation, Diversity, Item Ranking, User Satisfaction.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems ; User Profiling and Recommender Systems

Abstract: Over the last fifteen years, a large amount of research in recommender systems was devoted to the development of algorithms that focus on improving the accuracy of recommendations. More recently, it has been proposed that accuracy is not the only factor that contributes to the quality of recommender systems. Among others, the diversity of recommendation lists has been considered as one of the additionally relevant factors. Therefore a number of algorithms were proposed to generate recommendations lists containing a diverse set of items. However, limited research has been done regarding how to position those diverse items in the list. In this paper we therefore investigate how to organize the diverse items to achieve a higher perceived quality. The results of an experimental study show that the perceived diversity of a recommendation list depends on the placement of the diverse items. Placing the diverse items dispersedly or together at the bottom of the list can increase the perceive d diversity. In addition, we found that in the movie domain including diverse items in the recommendation list does not hurt user satisfaction, which means that recommender system providers have some flexibility to add some extra items to the lists, for example to increase the serendipity of the recommendations. (More)

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Paper citation in several formats:
Ge, M.; Jannach, D.; Gedikli, F. and Hepp, M. (2012). Effects of the Placement of Diverse Items in Recommendation Lists. In Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-8565-11-2; ISSN 2184-4992, SciTePress, pages 201-208. DOI: 10.5220/0003974802010208

@conference{iceis12,
author={Mouzhi Ge. and Dietmar Jannach. and Fatih Gedikli. and Martin Hepp.},
title={Effects of the Placement of Diverse Items in Recommendation Lists},
booktitle={Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2012},
pages={201-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003974802010208},
isbn={978-989-8565-11-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Effects of the Placement of Diverse Items in Recommendation Lists
SN - 978-989-8565-11-2
IS - 2184-4992
AU - Ge, M.
AU - Jannach, D.
AU - Gedikli, F.
AU - Hepp, M.
PY - 2012
SP - 201
EP - 208
DO - 10.5220/0003974802010208
PB - SciTePress