INTERTRASM - A Depth First Search Algorithm for Mining Intertransaction Association Rules

Dan Ungureanu, Alexandru Boicea

2008

Abstract

In this paper we propose an efficient method for mining frequent intertransaction itemsets. Our approach consists in mining maximal frequent itemsets (MFI) by extending the SmartMiner algorithm for the intertransaction case. We have called the new algorithm InterTraSM (Inter Transaction Smart Miner). Because it uses depth first search the memory needed by the algorithm is reduced; a strategy for passing tail information for a node combined with a dynamic reordering heuristic lead to improved speed. Experiments comparing InterTraSM to other existing algorithms for mining frequent intertransaction itemsets have revealed a significant gain in performance. Further development ideas are also discussed.

References

  1. Agrawal, R., Imielinski, T., Swami, A., 1993. Mining Association Rules Between Sets of Items in Large Databases. In Proc. of the ACM SIGMOD Conference on Management of Data.
  2. Agrawal, R., Srikant, R., 1994. Fast Algorithms for Mining Association Rules. In Proc. of the 20th Int'l Conference on Very Large Databases.
  3. Lu, H., Feng, L., Han, J., 2000. Beyond intratransaction association analysis: mining multidimensional intertransaction association rules. In ACM Transactions on Information Systems. Volume 18 , Issue 4.
  4. Tung, A.K.H., Lu, H., Feng, L., Han, J., 2003. Efficient mining of intertransaction association rules. In IEEE Transactions on Knowledge and Data Engineering. Volume 15, Issue 1.
  5. Lee, A.J.T., Wang, C-S., 2007. An efficient algorithm for mining frequent inter-transaction patterns. In Information Sciences: an International Journal. Volume 177, Issue 17.
  6. Lühr, S., West, G., Venkatesh, S., 2007. Recognition of emergent human behaviour in a smart home: A data mining approach. In Pervasive and Mobile Computing. Volume 3, Issue 2.
  7. Zou, Q., Chu, W., Lu, B., 2002. SmartMiner: a depth first algorithm guided by tail information for mining maximal frequent itemsets. In Proc. of the 2002 IEEE International Conference on Data Mining.
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Paper Citation


in Harvard Style

Ungureanu D. and Boicea A. (2008). INTERTRASM - A Depth First Search Algorithm for Mining Intertransaction Association Rules . In Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT, ISBN 978-989-8111-53-1, pages 148-153. DOI: 10.5220/0001880701480153


in Bibtex Style

@conference{icsoft08,
author={Dan Ungureanu and Alexandru Boicea},
title={INTERTRASM - A Depth First Search Algorithm for Mining Intertransaction Association Rules},
booktitle={Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT,},
year={2008},
pages={148-153},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001880701480153},
isbn={978-989-8111-53-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT,
TI - INTERTRASM - A Depth First Search Algorithm for Mining Intertransaction Association Rules
SN - 978-989-8111-53-1
AU - Ungureanu D.
AU - Boicea A.
PY - 2008
SP - 148
EP - 153
DO - 10.5220/0001880701480153