An efficient association rule mining for XML data

2006 SICE-ICASE International Joint Conference

Volumn , Issue , 2006, Pages 5782-5786

  Khaing, Myint Myint ^a   Thein, Nilar ^a  

^a UNIVERSITY OF COMPUTER STUDIES   (Myanmar)

Author keywords

Apriori algorithm; Association rules; Data mining

Indexed keywords

APRIORI ALGORITHMS; MEMORY STORAGE SIZE; RULE MINING;

ALGORITHMS; ASSOCIATION RULES; DATA STORAGE EQUIPMENT; PROBLEM SOLVING; XML;

DATA MINING;

EID: 34250778936     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SICE.2006.314676     Document Type: Conference Paper

References (17)

1. th International Conference on Information and Knowledge Management, 2000.
2. A. Terminer, M. C. Rouset, and M. Sebag, "TreeFinder: a First Step towards XML Data Mining", 2002, IEEE International Conference on Data Mining.
3. E.H.Han, G. Karypis and V. Kumer. "Sacalable Parallel Data Mining for Association rules". IEEE Transactions on Knowledge and Data Engineering, 12930:337-352, May/June 2000.
4. J.Park, D. Won, F. Fotouhi and U. Kin," ExiT-B: A new approach for extracting maximal frequent subtree from XML data:, IDEAL 2005.
5. J. S. Park, M. S. Chen and P. S. Yu. "Effective Hash-Based Algorithm for Mining Association Rules". In Proceeding of the 1995 ACM SIGMOD International Conference on Management of Data. Pages 175-186, San Joes, California, 1995.
6. J. Zhang, T. W. Ling, R. M. Bruckner, A. M. Tjoa, and H. Lui described on Effective Association Rule Mining from XML data. LNCS 3180,pp.494507.
7. J. S. park, M. S. Chen and P. S. Yu, "In Effective Hash Based Algorithm for Mining Association Rules", Dawak 2001. Springer_Verlag Berlin Hidelberg 2001.
8. K. Wang and H. Liu. Discovering typical structure of documents: A road map approach. In ACM SIGER Conference on Information Retrieval, 1998.
9. th ACM SIGKDD International Conference on Knowledge Discovery and Mining, Edmonton. Canada, July 2002.
10. th International Conference on VLDB, Santiago, Chile, September 1994.
11. R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. Inkeri Verkamo, "First Discovery of Association Rules", U. Fayyad et al., Advances in knowledge Discovery ans data mining, pp. 307-328, Menlo Park, Calf: AAAI Press, 1996.
12. th International Conference on Very Large Databases, pages 487-499. Santiago, Chile, 1994.
13. S. Orlando, P. Palmerini, and R. Perego. "Enhancing the Apriori Algorithm fr frequent Set Counting", DaWak 2001, LNCS 2114,pp.71 82, 2001. Springer Verlag Berlin Heidelberg 2001.
14. T. Asai, K. Arimura, H. Satamoto, and S. Arikawa, "Efficient Structure Discovery from Large Semi-Structured Data", Proceed Second SIAM International Conference Data mining, April, 2002.
15. Y. K. Woon and W. K. Ng, "A Support-Ordered Trie for Fast Frequent Itemset Discovery", IEEE TTRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL.16, No 7, JULY 2004.
16. nd International Conference on Web Information Systems Engineering, 2001.
17. th International Conference on Data Engineering, 2001.