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IJSTR >> Volume 8 - Issue 10, October 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A Case Study- Incremental Mining Algorithm On Library Transactional Database

[Full Text]

 

AUTHOR(S)

N.Satyavathi, Dr.B.Rama

 

KEYWORDS

Association rules, Borrowing patterns, Frequent item set mining, Incremental mining, Library database, Minimum support, Minimum confidence.

 

ABSTRACT

Association Rule Mining is one of the most essential techniques for mining frequent patterns. Many algorithms have been proposed for mining association rules by various researchers. Further various algorithms for incremental mining are developed. Recently developed, the FIN_INCRE algorithm is the incremental algorithms for mining frequent item sets, which updates mined association rules without rescanning the original database. In this paper, we explain how FIN_INCRE algorithm can be applied on the sample library transactional dataset to find out the borrowing patterns of books, which helps in stacking of books and selection of books for growth of departmental libraries. It then explains how the FIN-INCRE algorithm can be applied for updating borrowing without scanning original transactional database when four new transactions are added to the original transactional database.

 

REFERENCES

[1] Satyavathi N, Rama B, and Nagaraju A.,” Dynamically updating association rules: the Present state-of-the-art of index support for frequent itemset mining,” IJIRSET, Vol 4, issue July 2015 ISSN (online): 2319-8753, ISSN (print): 2347-6710
[2] W. Cheung, J. Han, V. T. Ng, and C. Y. Wong., “Maintenance of discovered association rules in large databases: An incremental updating technique” Proceedings of 12th International Conference on Data Engineering, pp. 106–114, 1996.
[3] W. Cheung, S. D. Lee, and B. Kao., “A general incremental technique for maintaining discovered association rules,” Proceedings of the 5th International Conference on Database System for Advanced Applications pp. 185–194, Melbourne, Australia. 1997.
[4] B. Xu, T. Yi, F. Wu, and Z. Chen. “An incremental updating algorithm for mining association rules,” Journal of Electronics, 19(4):403–407, 2002.
[5] B. Nath, D. K. Bhattacharyya, and A Ghosh., “Discovering association rules from incremental datasets,” International Journal of Computer Science and Communication, 1(2):433–441, 2010.
[6] Satyavathi N., Rama B., Nagaraju A., “Incremental Updating of Mined Association Rules for Reflecting Record Insertions,” Proceedings of the First International Conference on Computational Intelligence and Informatics. Advances in Intelligent Systems and Computing, vol 507. Springer, Singapore, pp 595-602.
[7] Deng, Z, and Lv, S., “Fast mining frequent item sets using nodesets,” Expert Systems with Applications, 41, pp. 4505-4512.