A recommender system for dynamically evolving online forums

Authors:
Carlos Castro-Herrera;Jane Cleland-Huang;Bamshad Mobasher
Affiliations:
DePaul University, Chicago, IL, USA;DePaul University, Chicago, IL, USA;Center for Web Intelligence, Chicago, IL, USA
Venue:
Proceedings of the third ACM conference on Recommender systems
Year:
2009

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Abstract

Recommender systems can be used in online forums to recommend discussion topics to users; however as these forums are characterized by a constant influx of new users and new posts, it is important to consider the performance of the recommender system under a scenario in which the internal composition of the items to be recommended, i.e., discussion threads, and the user preferences are constantly changing. In this paper we describe and evaluate a forum recommender designed to handle the challenges of dynamically evolving internet forums used to gather and discuss feature requests for various software products. In particular, we empirically show that two proposed enhancements to the representations of user profiles will result in improved recommendation effectiveness in dynamic environments.