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Concept Detection

Concept Detection. Amir R. Tahamtan. Concept Detection. Goals: discover knowledge, find associations. Discussed Techniques: Concept Mining , Document Clustering Related works: Keyword-based search , Resource discovery, Wrapper information extraction, Web queries, User preferences.

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Concept Detection

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  1. Concept Detection Amir R. Tahamtan Web Information Extraction

  2. Concept Detection • Goals:discover knowledge, find associations. • Discussed Techniques: Concept Mining, Document Clustering • Related works: Keyword-based search , Resource discovery, Wrapper information extraction, Web queries, User preferences Web Information Extraction

  3. Fu Y., Bauer T., Mostafa J., Palakal M., and Mukhopadhyay S (2002): Concept Extraction and Association from Cancer Literature. Proceedings of the 4th international workshop on Web information and data management. McLean, Virginia, USA. • Introduction • Algorithm • Experiments & Conclusion Web Information Extraction

  4. The Algorithm • Token discovery tf.idf : Wik= tik X log(N/nk) • LSA • Data representation as a term-doc matrix • Factoriziation : Xtx0 = Ttxr.Srxr.Orxo • Approximation : Xtx0 ˜X´tx0 = Ttxk.Skxk.Okxo • Token Association Discovery Web Information Extraction

  5. Web Information Extraction

  6. Web Information Extraction

  7. Liu B., Chin CW., Ng HAT (2003): Mining Topic-Specific Concepts and Definitions on the Web. Proceedings of the twelfth international conference on World Wide Web. Budapest, Hungary. • Introduction • The proposed Technique • System Architecture • Experiments & Conclusion Web Information Extraction

  8. The Proposed Technique • Algorithm Weblearn (T) • Subtopic Discovery • Definition Finding • Dealing with Ambiguity • Mutual Reinforcement Web Information Extraction

  9. System Architecture Web Information Extraction

  10. Web Information Extraction

  11. THANK YOU ! Web Information Extraction

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