A Layered Approach to Revisitation Prediction

  • George Papadakis
  • Ricardo Kawase
  • Eelco Herder
  • Claudia Niederée
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6757)

Abstract

Web browser users return to Web pages for various reasons. Apart from pages visited due to backtracking, they typically have a number of favorite/important pages that they monitor or tasks that reoccur on an infrequent basis. In this paper, we introduce the architecture of a system that facilitates revisitations through the effective prediction of the next page request. It consists of three layers, each dealing with a specific aspect of revisitation patterns: the first one estimates the value of each page by balancing the recency and the frequency of its requests; the second one captures the contextual regularities in users’ navigational activity in order to promote related pages, and the third one dynamically adapts the page associations of the second layer to the constant drift in the interests of users. For each layer, we introduce several methods, and evaluate them over a large, real-world dataset. The outcomes of our experimental evaluation suggest a significant improvement over other methods typically used in this context.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • George Papadakis
    • 1
    • 2
  • Ricardo Kawase
    • 2
  • Eelco Herder
    • 2
  • Claudia Niederée
    • 2
  1. 1.ICCS, National Technical Unversity of AthensGreece
  2. 2.L3S Research CenterLeibniz University of HanoverGermany

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