Climbing the app wall

Alexandros Karatzoglou, Linas Baltrunas, Karen Church, Matthias Böhmer
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
The explosive growth of the mobile application (app) market has made it difficult for users to find the most interesting and relevant apps from the hundreds of thousands that exist today. Context is key in the mobile space and so too are proactive services that ease user input and facilitate effective interaction. We believe that to enable truly novel mobile app recommendation and discovery, we need to support real context-aware recommendation that utilizes the diverse range of implicit mobile
more » ... ata available in a fast and scalable manner. In this paper we introduce the Djinn model, a novel context-aware collaborative filtering algorithm for implicit feedback data that is based on tensor factorization. We evaluate our approach using a dataset from an Android mobile app recommendation service called appazaar 1 . Our results show that our approach compares favorably with state-ofthe-art collaborative filtering methods.
doi:10.1145/2396761.2398683 dblp:conf/cikm/KaratzoglouBCB12 fatcat:xqzxsh7qqzeqddgt7wmlzkwrva