Mining positive and Negative Association Rules from interesting frequent and infrequent itemsets

Idheba Mohamad Ali O Swesi, Azuraliza Abu Bakar, Anis Suhailis Abdul Kadir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

Association rule mining is one of the most important tasks in data mining. The basic concept of association rules is to mine the interesting (positive) frequent patterns from a transaction database. However, mining the negative patterns has also attracted the attention of researchers in this area. The aim of this study is to develop a new model for mining interesting negative and positive association rules out of a transactional data set. The proposed model is an integration between two algorithms, the Positive Negative Association Rule (PNAR) algorithm and the Interesting Multiple Level Minimum Supports (IMLMS) algorithm, to propose a new approach (PNAR-IMLMS) for mining both negative and positive association rules from the interesting frequent and infrequent itemsets mined by the IMLMS model. The experimental results show that the PNAR-IMLMS model provides significantly better results than the previous model.

Original languageEnglish
Title of host publicationProceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
Pages650-655
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012 - Chongqing
Duration: 29 May 201231 May 2012

Other

Other2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
CityChongqing
Period29/5/1231/5/12

Fingerprint

Negative Association
Association Rules
Mining
Frequent Pattern
Model
Association Rule Mining
Transactions
Data Mining
Experimental Results

Keywords

  • frequent itemset
  • infrequent itemset
  • Negative association rule

ASJC Scopus subject areas

  • Control and Optimization
  • Logic

Cite this

Swesi, I. M. A. O., Abu Bakar, A., & Kadir, A. S. A. (2012). Mining positive and Negative Association Rules from interesting frequent and infrequent itemsets. In Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012 (pp. 650-655). [6234303] https://doi.org/10.1109/FSKD.2012.6234303

Mining positive and Negative Association Rules from interesting frequent and infrequent itemsets. / Swesi, Idheba Mohamad Ali O; Abu Bakar, Azuraliza; Kadir, Anis Suhailis Abdul.

Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012. 2012. p. 650-655 6234303.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Swesi, IMAO, Abu Bakar, A & Kadir, ASA 2012, Mining positive and Negative Association Rules from interesting frequent and infrequent itemsets. in Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012., 6234303, pp. 650-655, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012, Chongqing, 29/5/12. https://doi.org/10.1109/FSKD.2012.6234303
Swesi IMAO, Abu Bakar A, Kadir ASA. Mining positive and Negative Association Rules from interesting frequent and infrequent itemsets. In Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012. 2012. p. 650-655. 6234303 https://doi.org/10.1109/FSKD.2012.6234303
Swesi, Idheba Mohamad Ali O ; Abu Bakar, Azuraliza ; Kadir, Anis Suhailis Abdul. / Mining positive and Negative Association Rules from interesting frequent and infrequent itemsets. Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012. 2012. pp. 650-655
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