Smart Miner: A new framework for mining large scale web usage data

WWW'09 - Proceedings of the 18th International World Wide Web Conference

Volumn , Issue , 2009, Pages 161-170

  Bayir, Murat Ali ^a   Toroslu, Ismail Hakki ^b   Cosar, Ahmet ^b   Fidan, Guven ^c  

^a the State University of New York   (United States)

^b MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^c AGMLAB Information Technologies   (Turkey)

Author keywords

Graph mining; Map reduce; Parallel data mining; Web usage mining; Web user modeling

Indexed keywords

GRAPH MINING; MAP/REDUCE; PARALLEL DATA MINING; WEB USAGE MINING; WEB USERS;

DATA MINING; MINERS; WEB SERVICES; WEBSITES;

PROBLEM SOLVING;

EID: 77951174460     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1526709.1526732     Document Type: Conference Paper

References (28)

1. R. Agrawal and R. Srikant. Mining sequential patterns. In ICDE, pages 3-14, 1995.
2. M. A. Bayir, D. Guney, and T. Can. Integration of topological measures for eliminating non-specific interactions in protein interaction networks. Discrete Applied Mathematics, doi:10.1016/j.dam.2008.06.034, 2008.
3. J. Borges and M. Levene. Generating dynamic higher-order markov models in web usage mining. In PKDD, pages 34-45, 2005.
4. S. Brohée and J. van Helden. Evaluation of clustering algorithms for protein-protein interaction networks. BMC Bioinformatics, 7:488, 2006.
5. L. D. Catledge and J. E. Pitkow. Characterizing browsing strategies in the world-wide web. Computer Networks and ISDN Systems, 27(6):1065-1073, 1995.
6. D. Chakrabarti and C. Faloutsos. Graph mining: Laws, generators, and algorithms. ACM Comput. Surv., 38(1), 2006.
7. R. Cooley, B. Mobasher, and J. Srivastava. Web mining: Information and pattern discovery on the world wide web. In ICTAI, pages 558-567, 1997.
8. R. Cooley, B. Mobasher, and J. Srivastava. Data preparation for mining world wide web browsing patterns. Knowl. Inf. Syst., 1(1):5-32, 1999.
9. R. Cooley, P.-N. Tan, and J. Srivastava. Discovery of interesting usage patterns from web data. In WEBKDD, pages 163-182, 1999.
10. J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. In OSDI, pages 137-150, 2004.
11. D. Donato, L. Laura, S. Leonardi, and S. Millozzi. The web as a graph: How far we are. ACM Trans. Internet Techn., 7(1), 2007.
12. E. Frias-Martinez and V. Karamcheti. A customizable behavior model for temporal prediction of web user sequences. In WEBKDD, pages 66-85, 2002.
13. A. A. Ghorbani and X. Xu. A fuzzy markov model approach for predicting user navigation. In Web Intelligence, pages 307-311, 2007.
14. D. Godoy and A. Amandi. Learning browsing patterns for context-aware recommendation. In IFIP AI, pages 61-70, 2006.
15. J. Jung. Semantic preprocessing of web request streams for web usage mining. J. UCS, 11(8):1383-1396, 2005.
16. N. Khasawneh and C.-C. Chan. Active user-based and ontology-based web log data preprocessing for web usage mining. In Web Intelligence, pages 325-328, 2006.
17. R. Kumar, P. Raghavan, S. Rajagopalan, D. Sivakumar, A. Tomkins, and E. Upfal. The web as a graph. In PODS, pages 1-10, 2000.
18. O. Nasraoui, M. Soliman, E. Saka, A. Badia, and R. Germain. A web usage mining framework for mining evolving user profiles in dynamic web sites. IEEE Trans. Knowl. Data Eng., 20(2):202-215, 2008.
19. L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. tech. rep. computer systems laboratory. Technical report, Stanford University, Stanford, CA., 1998.
20. J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal, and M. Hsu. Mining sequential patterns by pattern-growth: The prefixspan approach. IEEE Trans. Knowl. Data Eng., 16(11):1424-1440, 2004.
21. C. Shahabi and F. B. Kashani. Efficient and anonymous web-usage mining for web personalization. INFORMS Journal on Computing, 15(2):123-147, 2003.
22. A. D. Silva, Y. Lechevallier, F. de A. T. de Carvalho, and B. Trousse. Mining web usage data for discovering navigation clusters. In ISCC, pages 910-915, 2006.
23. M. Spiliopoulou and L. Faulstich. Wum - a tool for www ulitization analysis. In WebDB, pages 184-103, 1998.
24. M. Spiliopoulou, B. Mobasher, B. Berendt, and M. Nakagawa. A framework for the evaluation of session reconstruction heuristics in web-usage analysis. INFORMS Journal on Computing, 15(2):171-190, 2003.
25. R. Srikant and R. Agrawal. Mining sequential patterns: Generalizations and performance improvements. In EDBT, pages 3-17, 1996.
26. J. Srivastava, R. Cooley, M. Deshpande, and P.-N. Tan. Web usage mining: Discovery and applications of usage patterns from web data. SIGKDD Explorations, 1(2):12-23, 2000.
27. R. B. T. O'Neill, F. Lavoie. Trends in the evolution of the public web. D-Lib Magazine, 9 Number:4, 2003.
28. M. Zaki. Spade: An efficient algorithm for mining frequent sequences. Machine Learning, 42:31-60, 2001.