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Adaptive Highlighting Of Links To Assist Surfing On The Internet

Author

Listed:
  • ZSOLT PALOTAI

    (Department of Information Systems, Pázmány Péter sétány 1/C, Budapest, Hungary H-1117, Hungary;
    Also at University of Technology and Economics, Pázmány Péter sétány 1/D, Budapest, Hungary H-1117, Hungary)

  • BÁLINT GÁBOR

    (Department of Information Systems, Eötvös Loránd University, Pázmány Péter sétány 1/C, Budapest, Hungary H-1117, Hungary)

  • ANDRÁS LŐRINCZ

    (Department of Information Systems, Eötvös Loránd University, Pázmány Péter sétány 1/C, Budapest, Hungary H-1117, Hungary)

Abstract

Gathering of novel information from the WWW constitutes a real challenge for artificial intelligence (AI) methods. Large search engines do not offer a satisfactory solution, their indexing cycle is long and they may offer a huge amount of documents. An AI-based assistant agent is studied here, which sorts the availabe links by their estimated value for the user. By using this link-list the best links could be highlighted in the browser, making the user's choices easier during surfing. The method makes use of (i) "experts", i.e. pre-trained text classifiers, forming the long-term memory of the system, (ii) relative values of experts and value estimation of documents based on recent choices of the user. Value estimation adapts fast and forms the short-term memory of the system. All experiments show that surfing based filtering can efficiently highlight 10%–20% of the documents in about five steps, or less.

Suggested Citation

  • Zsolt Palotai & Bálint Gábor & András Lőrincz, 2005. "Adaptive Highlighting Of Links To Assist Surfing On The Internet," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 117-139.
    • Handle: RePEc:wsi:ijitdm:v:04:y:2005:i:01:n:s0219622005001416
    DOI: 10.1142/S0219622005001416
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