Maintenance of IT-Tree for Transactions Deletion

  • Thien-Phuong LeEmail author
  • Bay Vo
  • Tzung-Pei Hong
  • Bac Le
  • Jason J. Jung
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 457)


Zaki et al. designed a mining algorithm based on the IT-tree structure, which traverses an IT-tree in depth-first order, generates itemsets by using the concept of equivalence classes, and rapidly computes the support of itemsets using tidset intersections. However, the transactions need to be processed batch-wise. In real-world applications, transactions are commonly changed. In this paper, we propose an algorithm for the management of the deleted transactions based on the IT-tree structure and pre-large concepts. Experimental results show that the proposed algorithm has a good performance.


Data mining frequent itemset incremental mining pre-large itemsets equivalence class IT-tree 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agrawal, R., Srikant, R.: Fast algorithm for mining association rules. In: The International Conference on Very Large Data Bases, pp. 487–499 (1994)Google Scholar
  2. 2.
    Cheung, D.W., Han, J., Ng, V.T., Wong, C.Y.: Maintenance of discovered association rules in large databases: An incremental updating approach. In: The Twelfth IEEE International Conference on Data Engineering, pp. 106–114 (1996)Google Scholar
  3. 3.
    Han, J., Pei, J., Yin, Y.: Mining frequent patterns without candidate generation. In: The 2000 ACM SIGMOD International Conference on Management of Data, pp. 1–12 (2000)Google Scholar
  4. 4.
    Hong, T.P., Wang, C.Y., Tao, Y.H.: A new incremental data mining algorithm using pre-large itemsets. Intelligent Data Analysis 5(2), 111–129 (2001)zbMATHGoogle Scholar
  5. 5.
    Hong, T.P., Lin, C.W., Wu, Y.L.: Incrementally fast updated frequent pattern trees. Expert Systems with Applications 34(4), 2424–2435 (2008)CrossRefGoogle Scholar
  6. 6.
    Koh, J.-L., Shieh, S.-F.: An Efficient Approach for Maintaining Association Rules Based on Adjusting FP-Tree Structures1. In: Lee, Y., Li, J., Whang, K.-Y., Lee, D. (eds.) DASFAA 2004. LNCS, vol. 2973, pp. 417–424. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Lin, C.W., Hong, T.P., Lu, W.H.: The Pre-FUFP algorithm for incremental mining. Expert Systems with Applications 36(5), 9498–9505 (2009)CrossRefGoogle Scholar
  8. 8.
    Lin, C.W., Hong, T.P., Lu, W.H.: Maintenance of the prelarge trees for record deletion. In: The Twelfth WSEAS International Conference on Applied Mathematics, pp. 105–110 (2007)Google Scholar
  9. 9.
    Le, T.P., Vo, B., Hong, T.P., Le, B.: Incremental mining frequent itemsets based on the trie structure and the prelarge itemsets. In: The 2011 IEEE International Conference on Granular Computing, pp. 369–373 (2011)Google Scholar
  10. 10.
    Le, T.P., Hong, T.P., Vo, B., Le, B.: An efficient incremental mining approach based on IT-tree. In: The 2012 IEEE International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future, pp. 57–61 (2012)Google Scholar
  11. 11.
    Li, X., Deng, Z.-H., Tang, S.: A Fast Algorithm for Maintenance of Association Rules in Incremental Databases. In: Li, X., Zaïane, O.R., Li, Z. (eds.) ADMA 2006. LNCS (LNAI), vol. 4093, pp. 56–63. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Vo, B., Hong, T.P., Le, B.: DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets. Expert Systems with Applications 39(8), 7196–7206 (2012)CrossRefGoogle Scholar
  13. 13.
    Zaki, M.J., Parthasarathy, S., Ogihara, M., Li, W.: New algorithms for fast discovery of association rules. In: The Third International Conference on Knowledge Discovery and Data Mining, pp. 283–286 (1997)Google Scholar
  14. 14.
    Zaki, M.J., Hsiao, C.J.: Efficient algorithms for mining closed itemsets and their lattice structure. IEEE Transactions on Knowledge and Data Engineering 17(4), 462–478 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thien-Phuong Le
    • 1
    Email author
  • Bay Vo
    • 2
  • Tzung-Pei Hong
    • 3
  • Bac Le
    • 4
  • Jason J. Jung
    • 5
  1. 1.Faculty of TechnologyPacific Ocean UniversityNhaTrang CityVietnam
  2. 2.Information Technology CollegeHo Chi MinhVietnam
  3. 3.Department of CSIENational University of KaohsiungKaohsing CityTaiwan, R.O.C.
  4. 4.Department of Computer ScienceUniversity of ScienceHo Chi MinhVietnam
  5. 5.Department of Computer EngineeringYeungnam UniversityYeungnamRepublic of Korea

Personalised recommendations