Abstract
It is generally recognized that information systems are becoming more complex and, therefore, intelligent user interfaces are needed to improve user interaction with these systems. Furthermore, the exponential growth of the Internet makes it difficult for the users to cope with the huge amount of available on-line information. The challenge that information providers and system engineers face is the creation of adaptive (Webbased) applications, as well as the development of “personalized” retrieval and filtering mechanisms. Responses to this challenge come from various disciplines including machine learning and data mining, intelligent agents and multi-agent systems, intelligent tutoring, information retrieval, etc.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Albrecht, D.W., Zukerman, I. and A.E. Nicholson: 1998. Bayesian Models for Keyhole Plan Recognition in an Adventure Game. User Modelling and User-Adapted Interaction 8, 5–47.
Balabanovic, M. and Y. Shoham: 1997. Content-Based, Collaborative Recommendation. Communications of the ACM 4(3), 66–72.
Basu, C., Hirsh, H., and W. Cohen: 1998. Recommendation as Classification: Using Social and Content-Based Information in Recommendation. Fifteenth National Conference in Artificial Intelligence, Madison, Wisconsin, MW.
Bauer, M.: 1999. From Interaction Data to Plan Libraries: A Clustering Approach. International Joint Conference on Artificial Intelligence, Stockholm, Sweden, 962–967.
Benaki, E., Karkaletsis, V. and C. D. Spyropoulos: 1997. Integrating User Modelling Into Information Extraction: The UMIE Prototype. Sixth International Conference on User Modelling, 55–57.
Billsus, D. and M. Pazzani: 1999. A Hybrid User Model for News Story Classsification Seventh International Conference on User Modelling, Banff, Canada, 99–108.
Bloedorn, E., Mani, I. and T. R. MacMillan: 1996. Machine Learning of User Profiles: Representational Issues. Thirteen National Conference on Artificial Intelligence, Portland, Oregon, 433–438.
Brajnik, G. and C. Tasso: 1994. A Shell for Developing Non-monotonic User Modelling Systems. International Journal of Human-Computer Studies 40, 31–62.
Brajnik, G., Guida, G. and C. Tasso: 1987. User Modelling in Intelligent Information Retrieval. Information Processing and Management 23, 305–320.
Brusilovsky, P., and E. Schwarz: 1997. User as Student: Towards an Adaptive Interface for Advanced Web Applications. Sixth International Conference on User Modelling, 177–188.
Chin, D.N.: 1989. KNOME: modelling what the user knows. In: A. Kobsa and W. Wahlster (eds.): User models in dialog systems. Berlin: Springer-Verlag, 74–107.
Chiu, B.C., and G. Webb.:1998. Using Decision Trees for Agent Modeling: Improving Prediction Performance. User Modelling and User-Adapted Interaction 8, 131–152.
Chiu, B.C., and G. Webb: “Dual-model: An Architecture for Utilizing Temporal Information in Student Modeling”. In [41].
Crabtree, I.B. and S.J. Soltysiak: 1998. Identifying and tracking changing interests. International Journal on Digital Libraries 2, 38–53.
Esposito, F., Malerba, D., Semeraro, G., Fanizzi, N. and S. Ferilli: 1998. Adding Machine Learning and Knowledge Intensive Techniques to a Digital Library Service. International Journal on Digital Libraries 2, 3–19.
Fragoudis, D. and S. Likothanassis: “User Modelling in Information Discovery: An Overview”. In [41].
Giangrandi P. and C. Tasso: 1997. Managing Temporal Knowledge in Student Modelling. Sixth International Conference on User Modelling, 415–426.
Joachims, T., Freitag, D. and T. Mitchell: 1997. WebWatcher: A tour guide for the World Wide Web. Fifteenth International Joint Conference in Artificial Intelligence, Nagoya, Aichi, Japan.
Kay, J.: 1995. The um Toolkit for Cooperative User Modelling. User Modelling and User Adapted Interaction 4, 149–196.
Langley, P.: 1999. User Modelling in Adaptive Interfaces. Seventh International Conference on User Modelling, Banff, Canada, 357–370.
Langley, P.: “User Modeling in Adaptive Interfaces”. In [41].
Maes, P.: 1994. Agents that Reduce Work and Information Overload. Communications of the ACM 37(7), 31–40.
Moukas, A.: 1997. Amalthaea: Information Discovery and Filtering using a Multiagent Evolving Ecosystem. Applied Artificial Intelligence: An International Journal 11(5), 437–457.
Moukas, A.: “User Modeling in a Multi-Agent Evolving System”. In [41].
Mueller, M.: 1999. Inducing Conceptual User Models. ABIS-99, 7. GI Workshop on Adaptivity and User Modelling in Interactive Software Systems.
Orwant, J.: 1995. Heterogeneous Learning in the DoppelgBAH:anger User Modeling System. User Modelling and User-Adapted Interaction 4, 107–130.
Paliouras, G., Karkaletsis, V., Papatheodorou, C., and C. D. Spyropoulos: 1999. Exploiting Learning Techniques for the Acquisition of User Stereotypes and Communities. Seventh International Conference on User Modelling, Banff, Canada, 169–178.
Paliouras, G., Papatheodorou, C., Karkaletsis, V., Tzitziras, P. and C.D. Spyropoulos: “Learning Communities of the ACAI’99 Web-site Visitors”. In [41].
Pazzani, M. and D. Billsus: 1997. Learning and Revising User Profiles: The Identification of Interesting Web Sites. Machine Learning 27, 313–331.
Perkowitz, M. and O. Etzioni: 1998. Adaptive Web Sites: Automatically synthesizing Web pages. Fifteen National Conference in Artificial Intelligence, Wisconsin, MW.
Perkowitz M., and O. Etzioni: 1999. Adaptive Web Sites: Conceptual Cluster Mining. Sixteenth International Joint Conference in Artificial Intelligence, Stockholm, Sweden, 264–269.
Raskutti, B. and A. Beitz: 1996. Acquiring User Preferences for Information Filtering in Interactive Multi-Media Services. Pacific Rim International Conference on Artificial Intelligence, 47–58.
Resnick, P. and H.R. Varian: 1997. Recommender Systems. Communications of the ACM 4(3), 56–58.
Rich, E.: 1983. Users are Individuals: Individualizing User Models. International Journal of Man-Machine Studies 18, 199–214.
Schwab, I. and W. Pohl: “Learning User Profiles from Positive Examples”. In [41].
Semeraro, G., Costabile, M.F., Esposito, F., Fanizzi, N. and S. Ferilli: “Machine Learning Techniques for Adaptive User Interfaces in a Corporate Digital Library Service”. In [41].
Sison, R., Numao, M. and M. Shimura: 1998. Discovering Error Classes from Discrepancies in Novice Behaviors via Multistrategy Conceptual Clustering. User Modelling and User-Adapted Interaction 8, 103–129.
Spiliopoulou, M., Faulstich, L. and K. Winkler: “A Data Miner Analyzingthe Navigational Behaviour of Web Users”. In [41].
Suryadi D. and P.J. Gmytrasiewicz: 1999. Learning Models of Other Agents Using Influence Diagrams. Seventh International Conference on User Modelling, Banff, Canada, 223–232.
Weber, G.: 1999. Adaptive Learning Systems in the World Wide Web. Seventh International Conference on User Modelling, Banff, Canada, 371–377.
Proceedings of the Workshop on Machine Learning in User Modeling, Advanced Course on Artificial Intelligence (ACAI’ 99), Chania, Greece, 1999 (http://www.iit.demokritos.gr/skel/eetn/acai99/Workshops.htm).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Papatheodorou, C. (2001). Machine Learning in User Modeling. In: Paliouras, G., Karkaletsis, V., Spyropoulos, C.D. (eds) Machine Learning and Its Applications. ACAI 1999. Lecture Notes in Computer Science(), vol 2049. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44673-7_17
Download citation
DOI: https://doi.org/10.1007/3-540-44673-7_17
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42490-1
Online ISBN: 978-3-540-44673-6
eBook Packages: Springer Book Archive