Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31103
A Web Designer Agent, Based On Usage Mining Online Behavior of Visitors

Authors: Babak Abedin, Babak Sohrabi


Website plays a significant role in success of an e-business. It is the main start point of any organization and corporation for its customers, so it's important to customize and design it according to the visitors' preferences. Also, websites are a place to introduce services of an organization and highlight new service to the visitors and audiences. In this paper, we will use web usage mining techniques, as a new field of research in data mining and knowledge discovery, in an Iranian government website. Using the results, a framework for web content layour is proposed. An agent is designed to dynamically update and improve web links locations and layout. Then, we will explain how it is used to directly enable top managers of the organization to influence on the arrangement of web contents and also to enhance customization of web site navigation due to online users' behaviors.

Keywords: Agent, Web Usage Mining, Website Design, website customization

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1628


[1] Kim,Wooju. Song,Yong U. Hong ,June S. "Web enabled expert systems using hyperlink-based inference (Accepted for publication)". Expert Systems with Applications. 2004. pp:1-13
[2] Michele Facca, Federico. Luca Lanzi, Pier. "Mining interesting knowledge from web logs: a survey". Data & Knowledge Engineering. Accepted for publication. 2004
[3] Hsu, Jeffrey. "Data mining trends and developments: The Key Data Mining Technologies and Applications for the 21st Century". Proc. of ISECON 2002
[4] Chakrabarti, Soumen. "Mining the web discovering knowledge form hypertext data". San Francisco, CA. Morgan Kaufmann Publishers An imprint of Elsevier Science 2003. pp: 1-13
[5] Arotaritei, Dragos. Mitra, Sushmita. "Web mining: a survey in the fuzzy framework". Fuzzy Sets and Systems: vol. 148, 2004. pp: 5-19
[6] Larsen, Jan. Lars Hansen, Kai. Szymkowiak Have, Anna. Christiansen, Torben. Kolenda, Thomas. "Webmining: learning from the World Wide Web". Computational Statistics & Data Analysis. 38. 2002. pp: 517-532
[7] Eirinaki, Magdalini. Vazirgiannis, Michalis. "Web Mining for Web Personalization". ACM Transactions on Internet Technology: vol. 3, no. 1, 2003. pp: 1-27.
[8] DeYoung, Colin G. Spence, Ian. "Profiling information technology users: en route to dynamic personalization". Computers in Human Behavior.. Vol. 20. 2004. pp: 55-65
[9] Cooley, R. Mobasher , B. and Srivastava, J. Web Mining: Information and Pattern Discovery on the World Wide Web. Proc of the 9th IEEE Int'l Conf. on Tools with Artificial Intelligence (ICTAI'97), 1997.
[10] Mobasher, B. Jain, N. Han, Eui Hong (Sam). Srivastava, J. "Web Mining: Pattern Discovery from World Wide Web Transactions". Technical Report TR96-050, Department of Computer Science, University of Minnesota, 1996.
[11] Theusinger, Christiane . Huber, Klaus-Peter. Analyzing the footsteps of your customers. Sixth ACM SIGKDD Internat. Conf. on Web KDD 2000.
[12] Ho Cho, Yoon. Kyeong Kim, Jae. Hie Kim, Soung. "A personalized recommender system based on web usage mining and decision tree induction". Expert Systems with Applications 23 .2002. 329-342
[13] Srivastava, Jaideep. Cooley, Robert. Deshpande, Mukund. Tan, Pang- Ning. "Web Usage Mining: Discovery and applications of usage patterns from web data". SIGKDD Explorations. ACM SIGKDD. Vol 1. Issue 2, 2000. pp: 12-23
[14] Albanese. Massimiliano, Picariello. Antonio, Sansone. Carlo, Sansone.Lucio, "A Web Personalization System based on Web Usage Mining Techniques". WWW2004, New York, USA. May 2004. pp: 288-289
[15] R. Kosala, H. Blockeel, "Web mining research: a survey", SIGKDD: SIGKDD explorations: newsletter of the special interest group (SIG) on knowledge discovery & data mining, ACM 2 (1). 2000. 1-15
[16] Y. Ivory. Melody , R. Sinha. Rashmi, A. Hearst. Marti. "Empirically Validated Web Page Design Metrics". SIGCHI-01, Seattle, WA, USA. April 2001. pp; 53-60
[17] Jin. Xin, Zhou. Yanzan, Mobasher. Bamshad, "Web Usage Mining Based on Probabilistic Latent Semantic Analysis", KDD-04, Seattle, Washington, USA. Aug- 2004. pp: 197-205
[18] J Decker, K., Sycara, K., Williamson, M., "Matchmaking and Brokering", In Proceedings of the second International Conference on Multi-Agent Systems, MIT Press/ AAAI Press. 1996
[19] Saeed M. H. "Reinforcement learning in Multi-Agent Systems" McGill university School of computer Science. 2001