Abstract
Recommender Systems have become a significant area in the context of web personalization, given the large amount of available data. Ontologies can be widely taken advantage of in recommender systems, since they provide a means of classifying and discovering of new information about the items to recommend, about user profiles and even about their context. We have developed a semantically enhanced recommender system based on this kind of ontologies. In this paper we present a description of the proposed system.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Adomavicius, G., Tuzhilin, A.: Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)
Mobasher, B., Jin, X., Zhou, Y.: Semantically Enhanced Collaborative Filtering on the Web. In: Berendt, B., Hotho, A., Mladenič, D., van Someren, M., Spiliopoulou, M., Stumme, G. (eds.) EWMF 2003. LNCS (LNAI), vol. 3209, pp. 57–76. Springer, Heidelberg (2004)
Middleton, S.E., Shadbolt, N., De Roure, D.: Ontological user profiling in recommender systems. ACM Trans. Inf. Syst. 22(1), 54–88 (2004)
Wang, R.-Q., Kong, F.-S.: Semantic-Enhanced Personalized Recommender System. In: International Conference on Machine Learning and Cybernetics, vol. 7, pp. 4069–4074 (2007)
Liu, P., Nie, G., Chen, D.: Exploiting Semantic Descriptions of Products and User Profiles for Recommender Systems. Computational Intelligence and Data Mining, 179–185 (2007)
Ziegler, C., Schmidt-Thieme, L., Lausen, G.: Exploiting semantic product descriptions for recommender systems. In: Proc. 2nd ACMSIGIR SemanticWeb and IR WS (2004)
Moshfeghi, Y., Agarwal, D., Piwowarski, B., Jose, J.M.: Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in Collaborative Filtering. In: Boughanem, M., et al. (eds.) ECIR 2009. LNCS, vol. 5478, pp. 54–65. Springer, Heidelberg (2009)
Linden, G., Smith, B., York, J.: Industry Report: Amazon.com Recommendations: Item-to-Item Collaborative Filtering. IEEE Distributed Systems Online 4(1) (2003)
Deshpande, M., Karypis, G.: Item-based top-n recommendation algorithms. ACM Trans. Inf. Sys. 22(1), 143–177 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ruiz-Montiel, M., Aldana-Montes, J.F. (2009). Semantically Enhanced Recommender Systems. In: Meersman, R., Herrero, P., Dillon, T. (eds) On the Move to Meaningful Internet Systems: OTM 2009 Workshops. OTM 2009. Lecture Notes in Computer Science, vol 5872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05290-3_74
Download citation
DOI: https://doi.org/10.1007/978-3-642-05290-3_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05289-7
Online ISBN: 978-3-642-05290-3
eBook Packages: Computer ScienceComputer Science (R0)