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An FAR-SW based approach for webpage information extraction

Author

Listed:
  • Zhan Bu

    (Nanjing University of Aeronautics and Astronautics
    The University of Alabama at Birmingham)

  • Chengcui Zhang

    (The University of Alabama at Birmingham)

  • Zhengyou Xia

    (Nanjing University of Aeronautics and Astronautics)

  • Jiandong Wang

    (Nanjing University of Aeronautics and Astronautics)

Abstract

Automatically identifying and extracting the target information of a webpage, especially main text, is a critical task in many web content analysis applications, such as information retrieval and automated screen reading. However, compared with typical plain texts, the structures of information on the web are extremely complex and have no single fixed template or layout. On the other hand, the amount of presentation elements on web pages, such as dynamic navigational menus, flashing logos, and a multitude of ad blocks, has increased rapidly in the past decade. In this paper, we have proposed a statistics-based approach that integrates the concept of fuzzy association rules (FAR) with that of sliding window (SW) to efficiently extract the main text content from web pages. Our approach involves two separate stages. In Stage 1, the original HTML source is pre-processed and features are extracted for every line of text; then, a supervised learning is performed to detect fuzzy association rules in training web pages. In Stage 2, necessary HTML source preprocessing and text line feature extraction are conducted the same way as that of Stage 1, after which each text line is tested whether it belongs to the main text by extracted fuzzy association rules. Next, a sliding window is applied to segment the web page into several potential topical blocks. Finally, a simple selection algorithm is utilized to select those important blocks that are then united as the detected topical region (main texts). Experimental results on real world data show that the efficiency and accuracy of our approach are better than existing Document Object Model (DOM)-based and Vision-based approaches.

Suggested Citation

  • Zhan Bu & Chengcui Zhang & Zhengyou Xia & Jiandong Wang, 2014. "An FAR-SW based approach for webpage information extraction," Information Systems Frontiers, Springer, vol. 16(5), pages 771-785, November.
    • Handle: RePEc:spr:infosf:v:16:y:2014:i:5:d:10.1007_s10796-013-9412-2
    DOI: 10.1007/s10796-013-9412-2
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    References listed on IDEAS

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    1. Bu, Zhan & Xia, Zhengyou & Wang, Jiandong & Zhang, Chengcui, 2013. "A last updating evolution model for online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2240-2247.
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    Cited by:

    1. Chengcui Zhang & Elisa Bertino & Bhavani Thuraisingham & James Joshi, 2014. "Guest editorial: Information reuse, integration, and reusable systems," Information Systems Frontiers, Springer, vol. 16(5), pages 749-752, November.

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