Abstract
User interest is one of personal traits attracting researchers’ attention in user modeling and user profiling. User interest competes with user knowledge to become the most important characteristics in user model. Adaptive systems need to know user interests so that provide adaptation to user. For example, adaptive learning systems tailor learning materials (lesson, example, exercise, test...) to user interests. I propose a new approach for discovering user interest based on document classification. The basic idea is to consider user interests as classes of documents. The process of classifying documents is also the process of discovering user interests.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines. Cambridge University Press, Cambridge (2000)
Mitchell, T.: Machine Learning. McGraw-Hill International, New York (1997)
Cortes, C., Vapnik, V.: Support vector networks. Machine Learning 20, 273–297 (1995)
Alrifai, M., Dolog, P., Nejdl, W.: Learner Profile Management for Collaborating Adaptive eLearning Applications. In: APS 2006: Joint International Workshop on Adaptivity, Personalization and the Semantic Web at the 17th ACM Hypertext 2006 conference, Odense, Denmark (August 2006)
Papatheodorou, C.: Machine Learning in User Modeling. In: Paliouras, G., Karkaletsis, V., Spyropoulos, C.D. (eds.) ACAI 1999. LNCS (LNAI), vol. 2049, pp. 286–294. Springer, Heidelberg (2001)
Rojas, R.: Neural Networks: A Systematic Introduction. Springer, Berlin (1996)
Lippmann, R.P.: An introduction to computing with neural nets. IEEE Transactions on Acoustics, Speech, and Signal Processing 1987 (1987)
Papatheodorou, C.: Machine Learning in User Modeling. In: Paliouras, G., Karkaletsis, V., Spyropoulos, C.D. (eds.) ACAI 1999. LNCS (LNAI), vol. 2049, pp. 286–294. Springer, Heidelberg (2001)
Han, J., Kamber, M.: Data Mining: Concepts and Techniques, 2nd edn. Elsevier Inc., Amsterdam (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Nguyen, L. (2010). Discovering User Interests by Document Classification. In: Ting, IH., Wu, HJ., Ho, TH. (eds) Mining and Analyzing Social Networks. Studies in Computational Intelligence, vol 288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13422-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-13422-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13421-0
Online ISBN: 978-3-642-13422-7
eBook Packages: EngineeringEngineering (R0)