Abstract
This paper improves a recently-presented approach to Web Personalization, named Community Web Directories, which applies personalization techniques to Web Directories. The Web directory is viewed as a concept hierarchy and personalization is realized by constructing user community models on the basis of usage data collected by the proxy servers of an Internet Service Provider. The user communities are modeled using Probabilistic Latent Semantic Analysis (PLSA), which provides a number of advantages such as overlapping communities, as well as a good rationale for the associations that exist in the data. The data that are analyzed present challenging peculiarities such as their large volume and semantic diversity. Initial results presented in this paper illustrate the effectiveness of the new method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anderson, C.R., Horvitz, E.: Web Montage: A Dynamic Personalized Start Page. In: 11th International World Wide Web Conference, Honolulu, Hawaii (2002)
Breese, J.S., Heckerman, D., Kadie, C.M.: Empirical Analysis of Predictive Algorithms for Collaborative Filtering. In: 14th Conference on Uncertainty in Artificial Intelligence, Madison, WI, USA, pp. 43–52 (1998)
Chaffee, J., Gauch, S.: Personal ontologies for web navigation. In: 9th Conference on Information and Knowledge Management, McLean, Virginia, USA, pp. 227–234 (2000)
Excite, http://www.excite.com
Hofmann, T.: Probabilistic Latent Semantic Analysis. In: 15th Conference on Uncertainty in Artificial Intelligence, San Francisco, CA, pp. 289–296 (1999)
Hofmann, T.: Learning What People (Don’t) Want. In: 12th European Conference in Machine Learning, pp. 214–225. Springer, Heidelberg (2001)
Jin, X., Zhou, Y., Mobasher, B.: Web usage mining based on probabilistic latent semantic analysis. In: SIGKDD international conference on Knowledge discovery and data mining (KDD 2004), Seattle, WA, USA, pp. 197–205 (2004)
Mobasher, B., Cooley, R., Srivastava, J.: Automatic personalization based on Web usage mining. Communications of the ACM 43(8), 142–151 (2000)
Open Directory Project, http://dmoz.org
Pierrakos, D., Paliouras, G., Papatheodorou, C., Spyropoulos, C.D.: Web Usage Mining as a Tool for Personalization: a survey. User Modeling and User-Adapted Interaction 13(4), 311–372 (2003)
Pierrakos, D., Paliouras, G., Papatheodorou, C., Karkaletsis, V., Dikaiakos, M.: Web Community Directories: A New Approach to Web Personalization. In: Berendt, B., et al. (eds.) EWMF 2003. LNCS (LNAI), vol. 3209, pp. 113–129. Springer, Heidelberg (2004)
Smyth, B., Cotter, C.: Personalized Adaptive Navigation for Mobile Portals. In: 15th European Conference on Artificial Intelligence. IOS Press, Amsterdam (2002)
Srivastava, J., Cooley, R., Deshpande, M., Tan, P.T.: Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. SIGKDD Explorations 1(2), 12–23 (2000)
Yahoo, http://www.yahoo.com
Zhao, Y., Karypis, G.: Evaluation of hierarchical clustering algorithms for document datasets. In: 11th Conference on Information and Knowledge Management, McLean, Virginia, USA, pp. 515–524 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pierrakos, D., Paliouras, G. (2005). Exploiting Probabilistic Latent Information for the Construction of Community Web Directories. In: Ardissono, L., Brna, P., Mitrovic, A. (eds) User Modeling 2005. UM 2005. Lecture Notes in Computer Science(), vol 3538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527886_13
Download citation
DOI: https://doi.org/10.1007/11527886_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27885-6
Online ISBN: 978-3-540-31878-1
eBook Packages: Computer ScienceComputer Science (R0)