Text associative classification approach for mining Arabic data set

Abdullah S. Ghareb, Abdul Razak Hamdan, Azuraliza Abu Bakar

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

6 Citations (Scopus)

Abstract

Text classification problem receives a lot of research that are based on machine learning, statistical, and information retrieval techniques. In the last decade, the associative classification algorithms which depends on pure data mining techniques appears as an effective method for classification. In this paper, we examine associative classification approach on the Arabic language to mine knowledge from Arabic text data set. Two methods of classification using AC are applied in this study; these methods are single rule prediction and multiple rule prediction. The experimental results against different classes of Arabic data set show that multiple rule prediction method outperforms single rule prediction method with regards to their accuracy. In general, the associative classification approach is a suitable method to classify Arabic text data set, and is able to achieve a good classification performance in terms of classification time and classification accuracy.

Original languageEnglish
Title of host publicationConference on Data Mining and Optimization
Pages114-120
Number of pages7
DOIs
Publication statusPublished - 2012
Event2012 4th Conference on Data Mining and Optimization, DMO 2012 - Langkawi
Duration: 2 Sep 20124 Sep 2012

Other

Other2012 4th Conference on Data Mining and Optimization, DMO 2012
CityLangkawi
Period2/9/124/9/12

Fingerprint

Data mining
Information retrieval
Learning systems

Keywords

  • Arabic text
  • associative classification
  • class association rule

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

Cite this

Ghareb, A. S., Hamdan, A. R., & Abu Bakar, A. (2012). Text associative classification approach for mining Arabic data set. In Conference on Data Mining and Optimization (pp. 114-120). [6329808] https://doi.org/10.1109/DMO.2012.6329808

Text associative classification approach for mining Arabic data set. / Ghareb, Abdullah S.; Hamdan, Abdul Razak; Abu Bakar, Azuraliza.

Conference on Data Mining and Optimization. 2012. p. 114-120 6329808.

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

Ghareb, AS, Hamdan, AR & Abu Bakar, A 2012, Text associative classification approach for mining Arabic data set. in Conference on Data Mining and Optimization., 6329808, pp. 114-120, 2012 4th Conference on Data Mining and Optimization, DMO 2012, Langkawi, 2/9/12. https://doi.org/10.1109/DMO.2012.6329808
Ghareb AS, Hamdan AR, Abu Bakar A. Text associative classification approach for mining Arabic data set. In Conference on Data Mining and Optimization. 2012. p. 114-120. 6329808 https://doi.org/10.1109/DMO.2012.6329808
Ghareb, Abdullah S. ; Hamdan, Abdul Razak ; Abu Bakar, Azuraliza. / Text associative classification approach for mining Arabic data set. Conference on Data Mining and Optimization. 2012. pp. 114-120
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