Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-45068-6_38
Title: Serendipitous recommendation for mobile apps using item-item similarity graph
Authors: Bhandari, U.
Sugiyama, K. 
Datta, A. 
Jindal, R.
Issue Date: 2013
Citation: Bhandari, U.,Sugiyama, K.,Datta, A.,Jindal, R. (2013). Serendipitous recommendation for mobile apps using item-item similarity graph. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8281 LNCS : 440-451. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-45068-6_38
Abstract: Recommender systems can provide users with relevant items based on each user's preferences. However, in the domain of mobile applications (apps), existing recommender systems merely recommend apps that users have experienced (rated, commented, or downloaded) since this type of information indicates each user's preference for the apps. Unfortunately, this prunes the apps which are releavnt but are not featured in the recommendation lists since users have never experienced them. Motivated by this phenomenon, our work proposes a method for recommending serendipitous apps using graph-based techniques. Our approach can recommend apps even if users do not specify their preferences. In addition, our approach can discover apps that are highly diverse. Experimental results show that our approach can recommend highly novel apps and reduce over-personalization in a recommendation list. © 2013 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/78348
ISBN: 9783642450679
ISSN: 03029743
DOI: 10.1007/978-3-642-45068-6_38
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