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Web Content Extraction Using Hybrid Approach

Author

Listed:
  • Dhumal Tanuja
  • Kumbhar Shital
  • Malave Sumedha
  • Salunkhe Shrutika

Abstract

Wide Web has rich source of voluminous and heterogeneous information which The World continues to expand in size and complexity. Many Web pages are unstructured and semi structured, so it consists of noisy information like advertisement, links, headers, footers etc. This noisy information makes extraction of Web content tedious. Extracting main content from web page is the preprocessing of web information system. Many techniques that were proposed for Web content extraction are based on automatic extraction and hand crafted rule generation. A hybrid approach is proposed to extract main content from Web pages. A HTML Web page is converted to DOM tree and features are extracted and with the extracted features, rules are generated. Decision tree classification and Naive Bayes classification are machine learning methods used for rules generation.

Suggested Citation

  • Dhumal Tanuja & Kumbhar Shital & Malave Sumedha & Salunkhe Shrutika, 2017. "Web Content Extraction Using Hybrid Approach," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(2), pages 1155-1159, April.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i2:id:hcseit1722178
    Note: Article URL: https://ijsrcseit.com/CSEIT1722178
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