Carlos Castro-Herrera
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.
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Digital Library
- C. Castro-Herrera, J. Cleland-Huang, and B. Mobasher. Enhancing stakeholder profiles to improve recommendations in online requirements elicitation. In IEEE Intl. Conf. on Requirements Engineering (RE'09), Atlanta, GA, USA, Aug. 2009. Google ScholarDigital Library
- C. Castro--Herrera, C. Duan, J. Cleland-Huang, and B. Mobasher. Using data mining and recommender systems to facilitate large-scale, open, and inclusive requirements elicitation processes. In IEEE Intl. Conf. on Requirements Engineering (RE'08), pages 165--168, Barcelona, Spain, Sept. 2008. Google ScholarDigital Library
- C. Castro-Herrera, C. Duan, J. Cleland-Huang, and B. Mobasher. A recommender system for requirements elicitation in large-scale software projects. In ACM Symposium on Applied Computing (SAC'09), pages 1419--1426, Honolulu, HI, USA, Mar. 2009. Google ScholarDigital Library
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Index Terms
- A recommender system for dynamically evolving online forums
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