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New Approach for Automated Categorizing and Finding Similarities in Online Persian News

  • Naser Ezzati Jivan
  • Mahlagha Fazeli
  • Khadije Sadat Yousefi
Part of the Communications in Computer and Information Science book series (CCIS, volume 96)

Abstract

The Web is a great source of information where data are stored in different formats, e.g., web-pages, archive files and images. Algorithms and tools which automatically categorize web-pages have wide applications in real-life situations. A web-site which collects news from different sources can be an example of such situations. In this paper, an algorithm for categorizing news is proposed. The proposed approach is specialized to work with documents (news) written in the Persian language but it can be easily generalized to work with documents in other languages, too. There is no standard test-bench or measure to evaluate the performance of this kind of algorithms as the amount of similarity between two documents (news) is not well-defined. To test the performance of the proposed algorithm, we implemented a web-site which uses the proposed approach to find similar news. Some of the similar news items found by the algorithm has been reported.

Keywords

Categorization of web pages category automatic categorization of Persian news feature similarity clustering structure of web pages 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Naser Ezzati Jivan
    • 1
  • Mahlagha Fazeli
    • 2
  • Khadije Sadat Yousefi
    • 2
  1. 1.National Library and Archives of the I.R of IranIran
  2. 2.Iranian University of Science and TechnologyIran

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