MAXLEN-FI: AN ALGORITHM FOR MINING MAXIMUM- LENGTH FREQUENT ITEMSETS FAST

Authors

  • Phan Thành Huấn The Information Technology Department, University of Social Sciences and Humanities, Vietnam National University-Ho Chi Minh City, Viet Nam http://orcid.org/0000-0002-2886-9352
  • Lê Hoài Bắc The Faculty of Information Technology, University of Natural Science, Vietnam National University-Ho Chi Minh City, Viet Nam

DOI:

https://doi.org/10.37569/DalatUniversity.8.2.407(2018)

Keywords:

Association rules, Frequent itemsets, Maximum length frequent itemsets.

Abstract

Association rule mining, one of the most important and well-researched techniques of data mining. Mining frequent itemsets are one of the most fundamental and most time-consuming problems in association rule mining. However, real-world applications are often sufficient to mine a small representative subset of frequent itemsets with low computational cost in generating association rules – maximum-length frequent itemsets. Maximum-length frequent itemsets can be useful in many application domains. In this paper, we proposed an algorithm called MAXLEN-FI for mining maximum-length frequent itemsets fast using an array of co-occurrence items. Finally, we presented experimental results on both synthetic and real-life datasets, which showed that the proposed algorithm performed better than the existing algorithms.

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References

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Published

01-07-2018

Volume and Issues

Section

Natural Sciences and Technology

How to Cite

Huấn, P. T., & Bắc, L. H. (2018). MAXLEN-FI: AN ALGORITHM FOR MINING MAXIMUM- LENGTH FREQUENT ITEMSETS FAST. Dalat University Journal of Science, 8(2), 109-123. https://doi.org/10.37569/DalatUniversity.8.2.407(2018)