Clustering items in different data sources induced by stability

International Arab Journal of Information Technology

Volumn 6, Issue 4, 2009, Pages 394-402

  Adhikari, Jhimli ^a   Rao, Pralhad ^b   Adhikari, Animesh ^c  

^a Narayan Zantye College   (India)

^b Department of Computer Science and Tecnology ^*  (India)

^c Chowgule College   (India)

Author keywords

Clustering; Data mining; Dispersion; Multiple databases; Stability

Indexed keywords

EID: 72449159738     PISSN: 16833198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (21)

1. Adhikari A. and Rao R., "Enhancing Quality of Knowledge Synthesized from Multi-Database Mining," Computer Journal of Pattern Recognition Letters, vol. 28, no. 16, pp. 2312-2324, 2007.
2. Adhikari A. and Rao R., "Synthesizing Heavy Association Rules from Different Real Data Sources," Computer Journal of Pattern Recognition Letters, vol. 29, no. 1, pp. 59-71, 2008.
3. Agrawal R., Imielinski T., and Swami A., "Mining Association Rules between Sets of Items in Large Databases," in Proceedings ACM SIGMOD Conference Management of Data, Canada, pp. 207-216, 1993.
4. Agrawal R. and Srikant R., "Fast Algorithms for Mining Association Rules," in Proceedings of 20th Very Large Databases (VLDB) Conference, Santiago, pp. 487-499, 1994.
5. Bluman G., Elementary Statistics: A Step by Step Approach, McGraw Hill, 2006.
6. Brockwell J. and Richard D., Introduction to Time Series and Forecasting, Springer, 2002.
7. Estivill V. and Yang J., "Fast and Robust General Purpose Clustering Algorithms," Computer Journal of Data Mining and Knowledge Discovery, vol. 8, no. 2, pp. 127-150, 2004.
8. Frequent Itemset Mining Dataset Repository, http://fimi.cs.helsinki.fi/data, 2004.
9. Han J., Pei J., and Yiwen Y., "Mining Frequent Patterns without Candidate Generation," in Proceedings ACM SIGMOD Conference Management of Data, New York, pp. 1-12, 2000.
10. Jain K., Murty N., and Flynn J., "Data Clustering: A Review," Computer Journal of ACM Computing Surveys, vol. 31, no. 3, pp. 264-323, 1999.
11. Leonard M. and Wolfe B., "Mining Transactional and Time Series Data," SUGI 30 Proceedings, UK, pp. 080-30, 2005.
12. Liu B., Ma Y., and Lee R., "Analyzing the Interestingness of Association Rules from the Temporal Dimension," IEEE International Conference on Data Mining, Silicon Valley, 377-384, 2001.
13. Liu L., Elements of Discrete Mathematics, McGraw-Hill, 1985.
14. Tan N., Kumar V., and Srivastava J., "Selecting the Right Interestingness Measure for Association Patterns," in Proceedings of SIGKDD Conference, Canada, pp. 32-41, 2002.
15. UCI ML Repository Content Summary, http://www.ics.uci.edu/~mlearn/MLSummary.html, 2002.
16. Wu X., Zhang C., and Zhang S., "Database Classification for Multi Database Mining," Computer Journal of Information Systems, vol. 30, no. 1, pp.71-88, 2005.
17. Wu X. and Zhang S., "Synthesizing High-Frequency Rules from Different Data Sources," Computer Journal of IEEE Transactions on Knowledge and Data Engineering, vol. 14, no.2, pp. 353-367, 2003.
18. Yang K. and Shahabi C., "On the Stationarity of Multivariate Time Series for Correlation-Based Data," in Proceedings of ICDM, Italy, pp. 805-808, 2005.
19. Zhang T., Ramakrishnan R., and Livny M., "BIRCH: A New Data Clustering Algorithm and Its Applications," Computer Journal of Data Mining and Knowledge Discovery, vol. 1, no. 2, pp. 141-182, 1997.
20. Zhang S., Wu X., and Zhang C., "Multi Database Mining," Computer Journal of IEEE Computational Intelligence Bulletin, vol. 2, no. 1, pp. 5-13, 2003.
21. Zhang S., Zhang C., and Wu X., Knowledge Discovery in Multiple Databases, Springer, 2004.