Triangle Counting Approach for graph-based Association Rules Mining

Yazan Alaya Jameel Al-Khassawneh, Azuraliza Abu Bakar, Suhaila Zainudin

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

1 Citation (Scopus)

Abstract

Graph-based Association Rules Mining (ARM) is a research area that represents a transactional database into a graph structure to optimize the search for frequent item sets. Sub-graph search is the process of pruning the search by looking for the best representation of connected nodes in a graph to represent the fully connected graphs. Triangle Counting Approach is one of the sub-graph search approaches to find the most represented graph. This study aims to employ the Triangle Counting Approach for graph-based association rules mining. A triangle counting method for graph-based ARM is proposed to prune the graph in the search for frequent item sets. The triangle counting is integrated with one of the graph-based ARM methods. It consists of four important phases; data representation, triangle construction, bit vector representation, and triangle integration with the graph-based ARM method. The performance of the proposed method is compared with the original graph-based ARM. Experimental results show that the proposed method reduces the execution time of rules generation and produces less number of rules with higher confidence.

Original languageEnglish
Title of host publicationProceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
Pages661-665
Number of pages5
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

Association Rule Mining
Triangle
Counting
Graph in graph theory
Graph Search
Frequent Itemsets
Subgraph
Rule Generation
Pruning
Execution Time
Confidence
Connected graph
Optimise

Keywords

  • Association Rules Mining
  • Data Representation
  • Graph-Based
  • Triangle Counting

ASJC Scopus subject areas

  • Control and Optimization
  • Logic

Cite this

Al-Khassawneh, Y. A. J., Abu Bakar, A., & Zainudin, S. (2012). Triangle Counting Approach for graph-based Association Rules Mining. In Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012 (pp. 661-665). [6233981] https://doi.org/10.1109/FSKD.2012.6233981

Triangle Counting Approach for graph-based Association Rules Mining. / Al-Khassawneh, Yazan Alaya Jameel; Abu Bakar, Azuraliza; Zainudin, Suhaila.

Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012. 2012. p. 661-665 6233981.

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

Al-Khassawneh, YAJ, Abu Bakar, A & Zainudin, S 2012, Triangle Counting Approach for graph-based Association Rules Mining. in Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012., 6233981, pp. 661-665, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012, Chongqing, 29/5/12. https://doi.org/10.1109/FSKD.2012.6233981
Al-Khassawneh YAJ, Abu Bakar A, Zainudin S. Triangle Counting Approach for graph-based Association Rules Mining. In Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012. 2012. p. 661-665. 6233981 https://doi.org/10.1109/FSKD.2012.6233981
Al-Khassawneh, Yazan Alaya Jameel ; Abu Bakar, Azuraliza ; Zainudin, Suhaila. / Triangle Counting Approach for graph-based Association Rules Mining. Proceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012. 2012. pp. 661-665
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