By Topic

A Hybrid Recommender System for Context-aware Recommendations of Mobile Applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wolfgang Woerndl ; Technische Universitaet Muenchen, Institut fuer Informatik. woerndl@in.tum.de ; Christian Schueller ; Rolf Wojtech

The goal of the work in this paper is towards the incorporation of context in recommender systems in the domain of mobile applications. The approach recommends mobile applications to users based on what other users have installed in a similar context. The idea is to apply a hybrid recommender system to deal with the added complexity of context. We have designed and realized the application to test our ideas. Users can select among several content-based or collaborative filtering components, including a rule-based module using information on point-of-interests in the vicinity of the user, and a component for the integration of traditional collaborative filtering. The implementation is integrated in a framework supporting the development and deployment of mobile services.

Published in:

Data Engineering Workshop, 2007 IEEE 23rd International Conference on

Date of Conference:

17-20 April 2007