Abstract
In this work a twofold algorithmic framework for the adaptation of web content to the users’ choices is presented. The main merits discussed are a) an optimal offline site adaptation – reorganization approach, which is based on a set of different popularity metrics and, additionally, b) an online personalization mechanism to emerge the most “hot” (popular and recent) site subgraphs in a recommendation list adaptive to the users” individual preferences.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
D. Avramouli, J. Garofalakis, D.J. Kavvadias, C. Makris, Y. Panagis, E. Sakkopoulos, “PopularWeb Hot Spots Identifiation and Visualization”, in the Fourteenth International World Wide Web Conference 2005 (WWW2005), Posters track, May 10–14, 2005, Chiba, Japan, pp. 912–913.
Boston Consulting Group, “Online Shopping Promises Consumers More than It Delivers”, Boston Consulting Group Study, 2000.
M.-S. Chen, J.S. Park, and P.S. Yu. Efficient Data mining for path traversal patterns. IEEE Trans. on Knowledge and Data Eng., 10(2), pp. 209–221, 1998.
Eleni Christopoulou, John Garofalakis, Christos Makris, Yannis Panagis, Evangelos Sakkopoulos, Athanasios Tsakalidis “Techniques and Metrics for Improving Website Structure”, Journal of Web Engineering, Rinton Press, 2, 1–2 pp. 09–104, 2003.
Eleni Christopoulou, John Garofalakis, Christos Makris, Yannis Panagis, Evangelos Sakkopoulos, Athanasios Tsakalidis, “Automating Restructuring of Web Applications”, ACM Hypertext 2002, June 11–15, 2002, College Park, Maryland, USA., ACM 1–58113-477–0/02/0006.
R. Cooley. Web Usage Mining: Discovery and Application of Interesting Patterns from Web data. PhD thesis, University of Minnesota, 2000.
Drott M.C. Using web server logs to improve site design Proceedings of ACM SIGDOC 98 pp. 43–50, 1998.
Garofalakis, J.D., Kappos, P. & Mourloukos, D.: Web Site Optimization Using Page Popularity. IEEE Internet Computing 3(4): 22–29 (1999)
John Garofalakis, Evangelos Sakkopoulos, Spiros Sirmakessis, Athanasios Tsakalidis “Integrating Adaptive Techniques into Virtual University Learning Environment”, IEEE International Conference on Advanced Learning Technologies, Full Paper, September 9–12, 2002, Kazan Tatarstan, Russia.
D.E. Knuth, Optimum Binary Search Trees. Acta Informatica, 1, 14–25, 1973.
K. Mehlhorn, Sorting and Searching. Data Structures and Algorithms, Vol. 1. EATCS Monographs in Theoretical Computer Science, Springer Verlag, 1984.
D.D. Sleator, and R.E. Tarjan. Self-Adjusting Binary Search Trees. Journal of the ACM, 32:3, 652–686, 1985.
R. Srikant, Y. Yang, Mining Web Logs to Improve Web Site Organization, in Proc. WWW01, pp. 430–437, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer
About this chapter
Cite this chapter
Makris, C., Panagis, Y., Sakkopoulos, E., Tsakalidis, A. (2006). An Algorithmic Framework for Adaptive Web Content. In: Sirmakessis, S. (eds) Adaptive and Personalized Semantic Web. Studies in Computational Intelligence, vol 14. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-33279-0_1
Download citation
DOI: https://doi.org/10.1007/3-540-33279-0_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30605-4
Online ISBN: 978-3-540-33279-4
eBook Packages: EngineeringEngineering (R0)