Abstract
The World Wide Web is an endless source of information and the information is mainly represented in the form of Web pages that the users may browse. The way that the users browse the Web depends on the factors like the attractiveness of the Web sites, their structure and navigational organization. The preferences of users are changing through time, which brings difficulties for building Web sites that best suit users’ profiles. Therefore, it is an important and challenging task to adapt the Web sites to the users’ needs. Adaptation of Web sites becomes more effective when it involves the semantic content of the Web pages. In this paper, a framework is proposed that aims to adapt both the topology and the ontology of the Web sites by using semantic content and Web usage mining techniques.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Achananuparp, P., Han, H., Nasraoui, O., Johnson, R.: Semantically enhanced user modeling. In: Proceedings of the 2007 ACM Symposium on Applied Computing (SAC ’07), pp. 1335–1339. ACM Press, New York (2007)
Coenen, F., Swinnen, G., Vanhoof, K., Wets, G.: A framework for self adaptive websites: tactical versus strategic changes. In: Proceedings of WEBKDD’2000 Web Mining for E-Commerce—Challenges and Opportunities, Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Boston, USA (2000)
Fink, J., Kobsa, A., Nill, A.: User-oriented adaptivity and adaptability in the AVANTI project. In: Proceedings of Conference Designing for the Web: Empirical Studies, Microsoft, Redmond (1996)
Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques. 3rd edn. Morgan Kaufmannm, San Francisco (2011)
Joachims, T., Freitag, D., Mitchell, T.: WebWatcher. A tour guide for the World Wide web. In: Proceedings of International Joint Conference on Artificial Intelligence, pp. 770–775. Nagoya, Japan (1997)
Kan, M.-Y., Thi, H.O.N.: Fast webpage classification using URL features. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management. New York, USA (2005)
Mikroyannidis, A., Theodoulidis, B.: A theoretical framework and an implementation architecture for self adaptive web sites. In: Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web, Intelligence, pp. 558–561 (2004)
Mikroyannidis, C.A., Theodoulidis, B.: Web usage driven adaptation of the semantic web. In: Proceedings of End User Aspects of the Semantic Web Workshop, 2nd European Semantic Web Conference, pp. 137–147. Heraklion, Greece (2005)
Perkowitz, M., Etzioni, O.: Adaptive web sites: an AI challenge. In: Proceedings of IJCAI-97. Nagoya, Japan (1997)
Perkowitz, M., Etzioni, O.: Towards adaptive web sites: conceptual framework and case study. Artif. Intell. 118(1–2), 245–275 (2000)
Wexelblat, A., Maes, P.: Footprints: History-rich tools for information foraging. In: Proceedings of Human Factors in Computing Systems (CHI), pp. 270–277. Pittsburgh, USA (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this paper
Cite this paper
Alkan, O.K., Senkul, P. (2013). New Techniques for Adapting Web Site Topology and Ontology to User Behavior. In: Gelenbe, E., Lent, R. (eds) Computer and Information Sciences III. Springer, London. https://doi.org/10.1007/978-1-4471-4594-3_43
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4594-3_43
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4593-6
Online ISBN: 978-1-4471-4594-3
eBook Packages: EngineeringEngineering (R0)