A Web usage mining framework for mining evolving user profiles in dynamic Web sites

IEEE Transactions on Knowledge and Data Engineering

Volumn 20, Issue 2, 2008, Pages 202-215

  Nasraoui, Olfa ^a,b   Soliman, Maha ^a,b   Saka, Esin ^a,b   Badia, Antonio ^a,b   Germain, Richard ^c  

^a IEEE

^b University of Louisville ^*  (United States)

^c UNIVERSITY OF LOUISVILLE   (United States)

Author keywords

Mining evolving clickstreams; Semantic Web mining; User profiles; Web usage mining

Indexed keywords

CUSTOMER RELATIONSHIP MANAGEMENT (CRM); INFORMATION FACETS; NONPROFIT ORGANIZATION; WEB USAGE MINING;

ONTOLOGY; REAL TIME SYSTEMS; SEARCH ENGINES; SEMANTIC WEB; USER INTERFACES; WEBSITES;

DATA MINING;

EID: 37549007987     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2007.190667     Document Type: Article

References (38)

1. R. Cooley, B. Mobasher, and J. Srivastava, "Web Mining: Information and Pattern Discovery on the World Wide Web," Proc. Ninth IEEE Int'l Conf Tools with AI (ICTAI '97), pp. 558-567, 1997.
2. O. Nasraoui, R. Krishnapuram, and A. Joshi, "Mining Web Access Logs Using a Relational Clustering Algorithm Based on a Robust Estimator," Proc. Eighth Int'l World Wide Web Conf (WWW '99), pp. 40-41, 1999.
3. O. Nasraoui, R. Krishnapuram, H. Frigui, and A. Joshi, "Extracting Web User Profiles Using Relational Competitive Fuzzy Clustering," Int'l J. Artificial Intelligence Tools, vol. 9, no. 4, pp. 509-526, 2000.
4. J. Srivastava, R. Cooley, M. Deshpande, and P.-N. Tan, "Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data," SIGKDD Explorations, vol. 1, no. 2, pp. 1-12, Jan. 2000.
5. M. Spiliopoulou and L.C. Faulstich, "WUM: A Web Utilization Miner," Proc. First Int'l Workshop Web and Databases (WebDB '98), 1998.
6. T. Yan, M. Jacobsen, H. Garcia-Molina, and U. Dayal, "From User Access Patterns to Dynamic Hypertext Linking," Proc. Fifth Int'l World Wide Web Conf (WWW '96), 1996.
7. M. Perkowitz and O. Etzioni, "Adaptive Web Sites: Automatically Learning for User Access Pattern," Proc. Sixth Int'l WWW Conf. (WWW '97), 1997.
8. J. Borges and M. Levene, "Data Mining of User Navigation Patterns," Web Usage Analysis and User Profiling, LNCS, H.A. Abbass, R.A. Sarker, and C.S. Newton, eds. pp. 92-111, Springer-Verlag, 1999.
9. O. Zaiane, M. Xin, and J. Han, "Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs," Proc. Advances in Digital Libraries (ADL '98), pp. 19-29, 1998.
10. O. Nasraoui and R. Krishnapuram, "A New Evolutionary Approach to Web Usage and Context Sensitive Associations Mining," Int'l J. Computational Intelligence and Applications, special issue on Internet intelligent systems, vol. 2, no. 3, pp. 339-348, Sept. 2002.
11. O. Nasraoui, C. Cardona, C. Rojas, and F. Gonzalez, "Mining Evolving User Profiles in Noisy Web Clickstream Data with a Scalable Immune System Clustering Algorithm," Proc. Workshop Web Mining as a Premise to Effective and Intelligent Web Applications (WebKDD '03), pp. 71-81, Aug. 2003.
12. P. Desikan and J. Srivastava, "Mining Temporally Evolving Graphs," Proc. Workshop Web Mining and Web Usage Analysis (WebKDD' 04), 2004.
13. O. Nasraoui, C. Rojas, and C. Cardona, "A Framework for Mining Evolving Trends in Web Data Streams Using Dynamic Learning and Retrospective Validation," Computer Networks, special issue on Web dynamics, vol. 50, no. 14, Oct. 2006.
14. M.A. Maloof and R.S. Michalski, "Learning Evolving Concepts Using Partial Memory Approach," Working Notes AAAI Fall Symp. Active Learning 1995, pp. 70-73, 1995.
15. M.A. Maloof and R.S. Michalski, "Selecting Examples for Partial Memory Learning," Machine Learning, vol. 41, no. 11, pp. 27-52, 2000.
16. T. Mitchell, R. Caruana, D. Freitag, J. McDermott, and D. Zabowski, "Experience with a Learning Personal Assistant," Comm. ACM, vol. 37, no. 7, pp. 80-91, 1994.
17. D. Billsus and M.J. Pazzani, "A Hybrid User Model for News Classification," Proc. Seventh Int'l Conf. User Modeling (UM '99), J. Kay, ed., pp. 99-108, 1999.
18. I. Grabtree and S. Soltysiak, "Identifying and Tracking Changing Interests," Int'l J. Digital Libraries, vol. 2, pp. 38-53,
19. J. Schlimmer and R. Granger, "Incremental Learning from Noisy Data," Machine Learning, vol. 1, no. 3, pp. 317-357, 1986.
20. G. Widmer and M. Kubat, "Learning in the Presence of Concept Drift and Hidden Contexts," Machine Learning, vol. 23, pp. 69-101, 1996.
21. I. Koychev, "Gradual Forgetting for Adaptation to Concept Drift," Proc. ECAI Workshop Current Issues in Spatio-Temporal Reasoning '00, pp. 101-106, 2000.
22. B. Mobasher, H. Dai, T. Luo, Y. Sung, and J. Zhu, "Integrating Web Usage and Content Mining for More Effective Personalization," Proc. Int'l Conf e-Commerce and Web Technologies (ECWeb '00), Sept. 2000.
23. R. Srikant and R. Agrawal, "Mining Generalized Association Rules," Proc. 21st Int'l Conf. Very Large Data Bases (VLDB '95), Sept. 1995.
24. S. Chakrabarti, B. Dom, R. Agrawal, and P. Raghavan, "Using Taxonomy, Discriminants, and Signatures for Navigation in Text Databases," Proc. 23rd Int'l Conf. Very Large Data Bases (VLDB '97), 1997.
25. H. Dai and B. Mobasher, "Using Ontologies to Discover Domain-Level Web Usage Profiles," Proc. Second ECML/PKDD Semantic Web Mining Workshop, 2002.
26. D. Oberle, B. Berendt, A. Hotho, and J. Gonzalez, "Conceptual User Tracking," Proc. First Int'l Atlantic Web Intelligence Conf. (AWIC '03), 2003.
27. B. Berendt and M. Spiliopoulou, "Analysis of Navigational Behavior in Web Sites Integrating Multiple Information Systems," VLDB J., vol. 9, no. 1, pp. 56-75, 2000.
28. M. Eirinaki, H. Lampos, M. Vazirgiannis, and I. Varlamis, "SEWeP: Using Site Semantics and a Taxonomy to Enhance the Web Personalization Process," Proc. ACM SIGKDD '03, Aug. 2003.
29. M. Levene, J. Borges, and G. Loizou, "Zipf's Law for Web Surfers," Knowledge and Information Systems, vol. 3, no. 1, pp. 120-129, Feb. 2001.
30. O. Nasraoui and R. Krishnapuram, "A Novel Approach to Unsupervised Robust Clustering Using Genetic Niching," Proc. Ninth IEEE Int'l Conf. Fuzzy Systems (FUZZ '00), pp. 170-175, May 2000.
31. J.H. Holland, Adaptation in Natural and Artificial Systems. MIT Press, 1975.
32. O. Resnik, "Semantic Similarity in a Taxonomy: An Information-Based Measure and Its Application to Problems of Ambiguity and Natural Language," J. Artificial Intelligence Research, vol. 11, pp. 95-130, 1999.
33. Z. Wu and M. Palmer, "Verb Semantics and Lexical Selection," Proc. 32nd Ann. Meeting of the Assoc. Computational Linguistics, pp. 133-138, June 1994.
34. D. Lin, "An Information-Theoretic Definition of Similarity," Proc. 15th Int'l Conf. Machine Learning (ICML '98), 1998.
35. C. Ziegler, G. Lausen, and L. Schmidt-Thieme, "Taxonomy-Driven Computation of Product Recommendations," Proc. 13th ACM Conf. Information and Knowledge Management (CIKM '04), pp. 406-415, 2004.
36. V. Cross, "Fuzzy Semantic Distance Measures between Ontological Concepts," Proc. Ann. Meeting North Am. Fuzzy Information Processing Soc. (NAFIPS '04), pp. 392-397, June 2004.
37. P. Ganesan, H. Garcia-Molina, and J. Widom, "Exploiting Hierarchical Domain Structure to Compute Similarity," ACM Trans. Information Systems, vol. 21, no. 1, pp. 64-93, 2003.
38. O. Nasraoui and S. Goswami, "Mining and Validating Localized Frequent Itemsets with Dynamic Tolerance," Proc. Sixth SIAM Int'l Conf Data Mining (SDM '06), pp. 578-582, Apr. 2006.