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Map-Based Recommendation of Hyperlinked Document Collections

  • Mieczysław A. Kłopotek
  • Sławomir T. Wierzchoń
  • Krzysztof Ciesielski
  • Michał Dramiński
  • Dariusz Czerski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4082)

Abstract

The increasing number of documents returned by search engines for typical requests makes it necessary to look for new methods of representation of the search results.

In this paper, we discuss the possibility to exploit incremental, navigational maps based both on page content, hyperlinks connecting similar pages and ranking algorithms (such as HITS, SALSA, PHITS and PageRank) in order to build visual recommender system. Such system would have an immediate impact on business information management (e.g. CRM and marketing, consulting, education and training) and is a major step on the way to information personalization.

Keywords

Recommender System Active Object Document Cluster Probabilistic Latent Semantic Analysis Node Utility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mieczysław A. Kłopotek
    • 1
  • Sławomir T. Wierzchoń
    • 1
  • Krzysztof Ciesielski
    • 1
  • Michał Dramiński
    • 1
  • Dariusz Czerski
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarszawaPoland

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