NEW FAST ALGORITHM FOR INCREMENTAL MINING OF ASSOCIATION RULES

Yasser El Sonbati, Rasha Kashef

Abstract

Mining association rules is a well-studied problem, and several algorithms were presented for finding large itemsets. In this paper we present a new algorithm for incremental discovery of large itemsets in an increasing set of transactions. The proposed algorithm is based on partitioning the database and keeping a summary of local large itemsets for each partition based on the concept of negative border technique. A global summary for the whole database is also created to facilitate the fast updating of overall large itemsets. When adding a new set of transactions to the database, the algorithm uses these summaries instead of scanning the whole database, thus reducing the number of database scans. The results of applying the new algorithm showed that the new technique is quite efficient, and in many respects superior to other incremental algorithms like Fast Update Algorithm (FUP) and Update Large Itemsets (ULI).

References

  1. Agrawal, R. ,Imielinski, T. and Swami, A., 1993. Mining Association Rules between Sets of Items in Large Databases. Proc. ACM SIGMOD. Int Conf, 1993.
  2. Agrawal, R. and Srikant, R..Fast Algorithms for Mining Association Rules .Proc.(VLDB).Int Conf, 1994.
  3. Cheung, D.W. Lee, S.D. and Kao, B. A General Incremental Technique for Maintaining Discovered Association Rules. Proc. Database systems for Advanced Applications, Int Conf, 1998.
  4. Park, J.S. Chen, M.S. and Yu, P.S.. Using a Hash Based Method with Transaction Trimming for Mining Association Rules. IEEE Trans on Knowledge and Data Engineering, 1997.
  5. Agrawal, C.C. and Yu, P.S. Mining Large Itemsets for Association Rules, Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 1998.
  6. Sarasere, A. Omiecinsky, E. and Navathe, S. An Efficient Algorithm for Mining Association Rules in Large Databases. Very Large Databases (VLDB). Int Conf. 1995.
  7. Hidber,C.Online Association Rule Mining.Proc.ACM SIGMOD Int Conf. Management of Data, 1998.
  8. Han, J. ,Pei, J. and Yin, Y. Mining frequent patterns without candidate generation. Proc. ACM SIGMOD. Int Conf. on management of Data,2000.
  9. Woon , Ng, Y. W. and Das, A. , Fast Online Association Rule Mining , IEEE transactions on Knowledge and Data Engineering ,2002.
  10. Sarda, N.L. and Srinivas, N. V.An Adaptive Algorithm for Incremental Mining of Association Rules. Proc .Database and Experts systems. Int Conf , 1998.
  11. Thomas, S., Bodagala, S. Alsabti, K. and Ranka, S.. An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases. Proc. Knowledge Discovery and Data Mining (KDD 97). Int conf, 1997.
  12. Aggarwal, C.C., Sun, Z. and Yu, P.S., Fast Algorithms for Online Generation of Profile Association Rules, IEEE transactions on knowledge and Data Engineering, September 2002.
  13. Cheung, D.W. Han, J. Ng, V.T. and Wong, C.Y. Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique. Proc. Data Engineering. Int Conf, 1996.
  14. Aggarwal, C. and Yu, P. A new Approach for Online Generation of Association Rules, IEEE transactions on Knowledge and Data Engineering, 2001
Download


Paper Citation


in Harvard Style

El Sonbati Y. and Kashef R. (2004). NEW FAST ALGORITHM FOR INCREMENTAL MINING OF ASSOCIATION RULES . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 972-8865-00-7, pages 275-281. DOI: 10.5220/0002624102750281


in Bibtex Style

@conference{iceis04,
author={Yasser El Sonbati and Rasha Kashef},
title={NEW FAST ALGORITHM FOR INCREMENTAL MINING OF ASSOCIATION RULES},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2004},
pages={275-281},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002624102750281},
isbn={972-8865-00-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - NEW FAST ALGORITHM FOR INCREMENTAL MINING OF ASSOCIATION RULES
SN - 972-8865-00-7
AU - El Sonbati Y.
AU - Kashef R.
PY - 2004
SP - 275
EP - 281
DO - 10.5220/0002624102750281