Abstract
This contribution presents a new approach to the representation of user’s interests and preferences. The adaptive user profile includes both interests given explicitly by the user, as a query, and also preferences expressed by the valuation of relevance of retrieved documents, so to express field independent translation between terminology used by user and terminology accepted in some field of knowledge. Procedures for building, modifying and using the profile, heuristic-based significant terms selection from relevant documents are presented. Experiments concerning the profile, as a personalization mechanism of Web search system, are presented and discussed.
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
Ambrosini, L., Cirillo, V., Micarelli, A.: A Hybrid Architecture for User-Adapted Information Filtering on the World Wide Web. In: Proc. of the 6th Int. Conf. on User Modeling, pp. 59–62. Springer, Heidelberg (1997)
Asnicar, F., Tasso, C.: ifWeb: a Prototype of User Model-Based Intelligent Agent for Document Filtering and Navigation in the World Wide Web. In: Proc. of the Workshop Adaptive Systems and User Modeling on the World Wide Web, UM 1997. Springer, Heidelberg (1997)
Billsus, D., Pazzani, M.: A Hybrid User Model for News Story Classification. In: Proc. of the 7th Int. Conf. on User Modeling, UM 1999, pp. 99–108. Springer, Heidelberg (1999)
Benaki, E., Karkaletsis, A., Spyropoulos, D.: User Modeling in WWW: the UMIE Prototype. In: Proc. of the 6th Int. Conf. on User Modeling, pp. 55–58. Springer, Heidelberg (1997)
Bhatia, S.J.: Selection of Search Terms Based on User Profile. Comm. of the ACM (1992)
Bull, S.: See Yourself Write: A Simple Student Model to Make Students Think. In: Proc. of the 6th Int. Conf. on User Modeling, pp. 315–326. Springer, Heidelberg (1997)
Collins, J.A., Greer, J.E., Kumar, V.S., McCalla, G.I., Meagher, P., Tkatch, R.: Inspectable User Models for Just–In Time Workplace Training. In: Proc. of the 6th Int. Conf. on User Modeling, pp. 327–338. Springer, Heidelberg (1997)
Daniłowicz, C.: Modelling of user preferences and needs in Boolean retrieval systems. Information Processing and Management 30(3), 363–378 (1994)
Davies, N.J., Weeks, R., Revett, M.C.: Information Agents for World Wide Web. In: Nwana, H.S., Azarmi, N. (eds.) Software Agents and Soft Computing: Towards Enhancing Machine Intelligence. LNCS(LNAI), vol. 1198, pp. 81–99. Springer, Heidelberg (1997)
Goldberg, J.L.: CDM: An Approach to Learning in Text Categorization. International Journal on Artificial Intelligence Tools 5(1 and 2), 229–253 (1996)
Indyka-Piasecka, A., Piasecki, M.: Adaptive Translation between User’s Vocabulary and Internet Queries. In: Proc. of the IIS IPWM 2003, pp. 149–157. Springer, Heidelberg (2003)
Danilowicz, C., Indyka-Piasecka, A.: Dynamic User Profiles Based on Boolean Formulas. In: Orchard, B., Yang, C., Ali, M. (eds.) IEA/AIE 2004. LNCS(LNAI), vol. 3029, pp. 779–787. Springer, Heidelberg (2004)
Jeapes, B.: Neural Intelligent Agents. Online & CDROM Rev. 20(5), 260–262 (1996)
Maglio, P.P., Barrett, R.: How to Build Modeling Agents to Support Web Searchers. In: Proc. of the 6th Int. Conf. on User Modeling, pp. 5–16. Springer, Heidelberg (1997)
Moukas, A., Zachatia, G.: Evolving a Multi-agent Information Filtering Solution in Amalthaea. In: Proc. of the Conference on Agents, Agents 1997. ACM Press, New York (1997)
Qiu, Y.: Automatic Query Expansion Based on a Similarity Thesaurus. PhD. Thesis (1996)
Salton, G., Bukley, C.: Term-Weighting Approaches in Automatic Text Retrieval. Information Processing & Management 24(5), 513–523 (1988)
Seo, Y.W., Zhang, B.T.: A Reinforcement Learning Agent for Personalised Information Filtering. In: Int. Conf. on the Intelligent User Interfaces, pp. 248–251. ACM, New York (2000)
Voorhees, E.M.: Implementing Agglomerative Hierarchic Clustering Algorithms for Use in Document Retrieval. Inf. Processing & Management 22(6), 465–476 (1986)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Indyka-Piasecka, A. (2011). Using Multi-attribute Structures and Significance Term Evaluation for User Profile Adaptation. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-23935-9_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23934-2
Online ISBN: 978-3-642-23935-9
eBook Packages: Computer ScienceComputer Science (R0)