Abstract
In this paper we present a comparative study of performance of an adaptive e-banking Web application supporting personalization either on a client or on a server side. Currently, modern applications being developed support various kinds of personalization. One of its types is changing behavior and appearance in response to actions taken by a user. Not only pre-defined rules but also new patterns discovered for different levels of events should be applied. Scaling such “interactive” applications to a large number of users is challenging. First, the stream of events generated by users’ actions may be huge, and second, processing of the adaptation rules per single user requires computing resources that multiply with the number of users.
This paper reports on the efficiency of the method enabling a client-side adaptation after moving adaptation logics from a server to a client.
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
Adomavicius, G., Tuzhilin, A.: Personalization technologies: a process-oriented perspective. Communications of the ACM 48(10), 83–90 (2005)
Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules in Large Databases. In: Proceedings of the 20th International Conference on Very Large Data Bases, VLDB 1994, pp. 487–499. Morgan Kaufmann Publishers Inc., San Francisco (1994), http://dl.acm.org/citation.cfm?id=645920.672836
Atterer, R., Wnuk, M., Schmidt, A.: Knowing the user’s every move: user activity tracking for website usability evaluation and implicit interaction. In: Proceedings of the 15th International Conference on World Wide Web, WWW 2006, pp. 203–212. ACM, New York (2006), http://doi.acm.org/10.1145/1135777.1135811
Brusilovsky, P., Kobsa, A., Vassileva, J. (eds.): Adaptive Hypertext and Hypermedia. Springer (1998) ISBN 978-0-7923-4843-6
De Virgilio, R., Torlone, R., Houben, G.J.: A Rule-based Approach to Content Delivery Adaptation in Web Information Systems. In: Proceedings of the 7th International Conference on Mobile Data Management, MDM 2006, p. 21. IEEE Computer Society, Washington, DC (2006), http://dx.doi.org/10.1109/MDM.2006.16
Gao, C., Wei, J., Xu, C., Cheung, S.C.: Sequential event pattern based context-aware adaptation. In: Proceedings of the Second Asia-Pacific Symposium on Internetware, Internetware 2010, pp. 3:1–3:8. ACM, New York (2010), http://doi.acm.org/10.1145/2020723.2020726
Mueller, F., Lockerd, A.: Cheese: tracking mouse movement activity on websites, a tool for user modeling. In: CHI 2001 Extended Abstracts on Human Factors in Computing Systems, CHI EA 2001, pp. 279–280. ACM, New York (2001), http://doi.acm.org/10.1145/634067.634233
Paskalev, P.: Rule based GUI modification and adaptation. In: Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, CompSysTech 2009, pp. 93:1–93:7. ACM, New York (2009), http://doi.acm.org/10.1145/1731740.1731841
Paskalev, P., Serafimova, I.: Rule based framework for intelligent GUI adaptation. In: Proceedings of the 12th International Conference on Computer Systems and Technologies, CompSysTech 2011, pp. 101–108. ACM, New York (2011), http://doi.acm.org/10.1145/2023607.2023626
Schneider-Hufschmidt, M., Kühme, T., Malinowski, U. (eds.): Adaptive User Interfaces: Principles and Practice. Human Factors in Information Technology. North Holland (1993) ISBN 978-0-444-81545-3
Wang, H., Mehta, R., Supakkul, S., Chung, L.: Rule-based context-aware adaptation using a goal-oriented ontology. In: Proceedings of the 2011 International Workshop on Situation Activity & Goal Awareness, SAGAware 2011, pp. 67–76. ACM, New York (2011), http://doi.acm.org/10.1145/2030045.2030061
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Węcel, K., Kaczmarek, T., Filipowska, A. (2012). Scalable Adaptation of Web Applications to Users’ Behavior. In: Nguyen, NT., Hoang, K., Jȩdrzejowicz, P. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2012. Lecture Notes in Computer Science(), vol 7654. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34707-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-34707-8_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34706-1
Online ISBN: 978-3-642-34707-8
eBook Packages: Computer ScienceComputer Science (R0)