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Model for Automatic Textual Data Clustering in Relational Databases Schema

  • Wael M.S. Yafooz
  • Siti Z.Z. Abidin
  • Nasiroh Omar
  • Rosenah A. Halim
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 285)

Abstract

In the last two decades, unstructured information has become a major challenge in information management. Such challenge is caused by the massive and increasing amount of information resulting from the conversion of almost all daily tasks into digital format. Tools and applications are necessary in organizing unstructured information, which can be found in structured data, such as in relational database management systems (RDBMS). RDBMS has robust and powerful structures for managing, organizing, and retrieving data. However, structured data still contains unstructured information. In this paper, the methods used for managing unstructured data in RDBMS are investigated. In addition, an incremental and dynamic repository for managing unstructured data in relational databases are introduced. The proposed technique organizes unstructured information through linkages among textual data based on semantics. Furthermore, it provides users with a good picture of the unstructured information. The proposed technique can rapidly and easily obtain useful data, and thus, it can be applied in numerous domains, particularly those who deal with textual data, such as news articles.

Keywords

Relational databases Unstructured data Document clustering Query efficiency Textual data 

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Notes

Acknowledgments

The authors wish to thank Universiti Teknologi MARA(UiTM) for the financial support. This work was supported in part by a grant number 600-RMI-/DANA 5/3/RIF (498/2012).

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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  • Wael M.S. Yafooz
    • 1
  • Siti Z.Z. Abidin
    • 1
  • Nasiroh Omar
    • 1
  • Rosenah A. Halim
    • 1
  1. 1.Faculty of Computer and Mathematical SciencesUiTMSelagorMalaysia

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