A Web Designer Agent, Based On Usage Mining Online Behavior of Visitors
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.
[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
[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
@article{"International Journal of Business, Human and Social Sciences:63485", author = "Babak Abedin and Babak Sohrabi", title = "A Web Designer Agent, Based On Usage Mining Online Behavior of Visitors", abstract = "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 = "Web usage mining, website design, agent, website
customization.", volume = "1", number = "6", pages = "284-5", }
