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PDC-Transitive: An Enhanced Heuristic for Document Clustering Based on Relational Analysis Approach and Iterative MapReduce

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  • Yasmine Lamari

    (Department of Computer Science, Faculty of Science of Rabat, Mohammed V University, 4 Avenue Ibn Battouta B. P. 1014 RP, Rabat, Morocco)

  • Said Chah Slaoui

    (Department of Computer Science, Faculty of Science of Rabat, Mohammed V University, 4 Avenue Ibn Battouta B. P. 1014 RP, Rabat, Morocco)

Abstract

Recently, MapReduce-based implementations of clustering algorithms have been developed to cope with the Big Data phenomenon, and they show promising results particularly for the document clustering problem. In this paper, we extend an efficient data partitioning method based on the relational analysis (RA) approach and applied to the document clustering problem, called PDC-Transitive. The introduced heuristic is parallelised using the MapReduce model iteratively and designed with a single reducer which represents a bottleneck when processing large data, we improved the design of the PDC-Transitive method to avoid the data dependencies and reduce the computation cost. Experiment results on benchmark datasets demonstrate that the enhanced heuristic yields better quality results and requires less computing time compared to the original method.

Suggested Citation

  • Yasmine Lamari & Said Chah Slaoui, 2018. "PDC-Transitive: An Enhanced Heuristic for Document Clustering Based on Relational Analysis Approach and Iterative MapReduce," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-18, June.
    • Handle: RePEc:wsi:jikmxx:v:17:y:2018:i:02:n:s0219649218500211
    DOI: 10.1142/S0219649218500211
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    References listed on IDEAS

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    1. Gunasekaran Manogaran & Daphne Lopez, 2017. "Disease Surveillance System for Big Climate Data Processing and Dengue Transmission," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 8(2), pages 88-105, April.
    2. Arushi Jain & Vishal Bhatnagar, 2017. "Concoction of Ambient Intelligence and Big Data for Better Patient Ministration Services," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 8(4), pages 19-30, October.
    3. Hanan Al-Mofareji & Mahmoud Kamel & Mohamed Y. Dahab, 2017. "WeDoCWT: A New Method for Web Document Clustering Using Discrete Wavelet Transforms," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-19, March.
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