Folkommender: a group recommender system based on a graph-based ranking algorithm

With the rapid popularity of smart devices, users are easily and conveniently accessing rich multimedia content. Consequentially, the increasing need for recommender services, from both individual users and groups of users, has arisen. In this paper, we present a new graph-based approach to a recomm...

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Vydané v:Multimedia systems Ročník 19; číslo 6; s. 509 - 525
Hlavní autori: Kim, Heung-Nam, Bloess, Mark, El Saddik, Abdulmotaleb
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2013
Predmet:
Computer Communication Networks
Computer Graphics
Computer Science
Cryptology
Data Storage Representation
Operating Systems
Regular Paper
Social recommender system
Graph-based recommendation
Group recommendation
Random walk with restarts
ISSN:0942-4962, 1432-1882
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Popis
Shrnutí:With the rapid popularity of smart devices, users are easily and conveniently accessing rich multimedia content. Consequentially, the increasing need for recommender services, from both individual users and groups of users, has arisen. In this paper, we present a new graph-based approach to a recommender system, called Folkommender , that can make recommendations most notably to groups of users. From rating information, we first model a signed graph that contains both positive and negative links between users and items. On this graph we examine two distinct random walks to separately quantify the degree to which a group of users would like or dislike items. We then employ a differential ranking approach for tailoring recommendations to the group. Our empirical evaluations on two real-world datasets demonstrate that the proposed group recommendation method performs better than existing alternatives. We also demonstrate the feasibility of Folkommender for smartphones.
ISSN:0942-4962
1432-1882
DOI:10.1007/s00530-012-0298-5