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Personalized Detection of Fresh Content and Temporal Annotation for Improved Page Revisiting

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Database and Expert Systems Applications (DEXA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4080))

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Abstract

Page revisiting is a popular browsing activity in the Web. In this paper we describe a method for improving page revisiting by detecting and highlighting the information on browsed Web pages that is fresh for a user. Content freshness is determined based on comparison with the previously viewed versions of pages. Any new content for the user is marked, enabling the user to quickly spot it. We also describe a mechanism for visually informing users about the degree of freshness of linked pages. By indicating the freshness level of content on linked pages, the system enables users to navigate the Web more effectively. Finally, we propose and demonstrate the concept of determining user-dependent, subjective age of page contents. Using this method, elements of Web pages are annotated with dates indicating the first time the elements were accessed by the user.

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Author information

Authors and Affiliations

  1. Kyoto University, Yoshida-Honmachi, Sakyo-ku, 606-8501, Kyoto, Japan

    Adam Jatowt & Katsumi Tanaka

  2. Kyoto Sangyo University, Motoyama, Kamigamo, Kita-Ku, 603-8555, Kyoto, Japan

    Yukiko Kawai

Authors
  1. Adam Jatowt
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  2. Yukiko Kawai
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  3. Katsumi Tanaka
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Editor information

Editors and Affiliations

  1. School of Computing, National University of Singapore,  

    Stéphane Bressan

  2. University of Linz, Altenbergerstraße 69, 4040, Linz, Austria

    Josef Küng  & Roland Wagner  & 

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© 2006 Springer-Verlag Berlin Heidelberg

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Jatowt, A., Kawai, Y., Tanaka, K. (2006). Personalized Detection of Fresh Content and Temporal Annotation for Improved Page Revisiting. In: Bressan, S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2006. Lecture Notes in Computer Science, vol 4080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11827405_81

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  • DOI: https://doi.org/10.1007/11827405_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37871-6

  • Online ISBN: 978-3-540-37872-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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