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A Method for Web-Based User Interface Recommendation Using Collective Knowledge and Multi-attribute Structures

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6922))

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Abstract

This paper presents a framework of a method for the problem of web-based user interface personalization and recommendation using collective knowledge (coming from s collection of existing users) and multi-attribute and multi-value structures. In this method a user profile consists of user data and system usage path. For a new user the usage path is determined basing on the paths used by previous users (the collective knowledge). This approach involving the recommendation methods may be applied in many systems which require such mechanisms. The structure of user profile and an algorithm for recommendation are presented.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, The State Higher Vocational School in Nysa, ArmiiKrajowej 7 Street, 48-300, Nysa, Poland

    Michał Malski

Authors
  1. Michał Malski
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Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Morska 81-87, 81-225, Gdynia, Poland

    Piotr Jędrzejowicz

  2. Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. University of Information Technology Vietnam, Km 20, Xa lo Ha Noi, Linh Trung, Thu Duc, 848, HCM City, Vietnam

    Kiem Hoang

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Malski, M. (2011). A Method for Web-Based User Interface Recommendation Using Collective Knowledge and Multi-attribute Structures. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_34

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  • DOI: https://doi.org/10.1007/978-3-642-23935-9_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23934-2

  • Online ISBN: 978-3-642-23935-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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