A Web page prediction model based on click-stream tree representation of user behavior

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2003, Pages 535-540

  Gündüz, Sule ^a   Zsu, M Tamer ^b  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Graph based clustering; Two dimensional sequential model; Web usage mining

Indexed keywords

CACHE PREFETCHING; CLUSTER-BASED; DATA SETS; FREQUENT SEQUENCES; GRAPH BASED CLUSTERING; HIGHER ORDER; MARKOV MODEL; NEW MODEL; NUMBER OF STATE; PREDICTION MODEL; SEQUENCE MINING; SEQUENTIAL MODEL; SEQUENTIAL PATTERNS; SEQUENTIAL-PATTERN MINING; SIMILARITY MEASURE; TIME SPENT; TREE REPRESENTATION; USER BEHAVIORS; USER SESSIONS; WEB PAGE; WEB USAGE MINING;

BEHAVIORAL RESEARCH; FORECASTING; HYDRAULICS; MARKOV PROCESSES; MATHEMATICAL MODELS; TWO DIMENSIONAL; WORLD WIDE WEB;

DATA MINING;

EID: 48649102014     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/956750.956815     Document Type: Conference Paper

References (14)

1. R. Agrawal and R. Srikant. Mining sequential patterns. In Proceedings of the International Conference on Data Engineering (ICDE), March 1995. Taipei, Taiwan.
2. A. Banerjee and J. Ghosh. Clickstream clustering using weighted longest common subsequences. In Proceedings of the Wokshop on Web Mining, SIAM Conference on Data Mining, pages 33-40, 2001. Chicago, IL.
3. K. Cahrter, J. Schaeffer, and D. Szafron. Sequence alignment using fastlsa. In Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS'2000), pages 239-245, 2000.
4. Cluto. http://wwwusers.cs.umn.edu/karypis/cluto/index.html.
5. Dan Cosley, Steve Lawrence, and David M. Pennock. REFEREE: An open framework for practical testing of recommender systems using researchindex. In Proceedings of 28th International Conference on Very Large Databases, VLDB 2002, Hong Kong, August 20-23 2002.
6. Chris Ding, Xiaofeng He, Hongyuan Zha, Minh Gu, and Horst Simon. Spectral min-max cut for graph partitioning and data clustering. 2001. Technical Report TR-2001-XX, Lawrence Berkeley National Laboratory, University of CaliforniaBerkeley, CA.
7. O. Etzioni. The world wide web: Quagmire or gold mine. Communications of the ACM, 39 (11):65-68, 1996.
8. ClarkNet WWW Server Log. http://ita.ee.lbl.gov/html/contrib/ClarkNet- HTTP.html.
9. NASA Kennedy Space Center Log. http://ita.ee.lbl.gov/html/contrib/NASA- HTTP.html.
10. B. Mobasher, H. Dai, T. Luo, and M. Nakagawa. Discovery of aggregate usage profiles for web personalization. In Proceedings of the Web Mining for E-Commerce Workshop (WebKDD'2000), 2000.
11. B. Mobasher, H. Dai, T. Luo, and M. Nakagawa. Effective personalization based on association rule discovery from web usage data. In Proceedings of the 3rd ACM Workhop on Web Information and Data Management, November 2001. Atlanta, USA.
12. R. R. Sarukkai. Link prediction and path analysis using markov chains. In Proceedings of the Ninth International World Wide Web Conference, 2000. Amsterdam.
13. C. Shahabi, A. Zarkesh, J. Adibi, and V. Shah. Knowledge discovery from users web-page navigation. In Proceeding of the IEEE RIDE97 Workshop, pages 20-29, April 1997. Birmingham, England.
14. J. Srivastava, R. Cooley, M. Deshpande, and P. N. Tan. Web usage mining: Discovery and application of usage patterns from web data. ACM SIGKDD Explorations, 1 (2):12-23, 2000.