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Modeling User’s Non-functional Preferences for Personalized Service Ranking

  • Rozita Mirmotalebi
  • Chen Ding
  • Chi-Hung Chi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7636)

Abstract

Modeling users’ online behavior has great benefit for many e-Commerce web sites and search engines. In the context of software service selection, if we could understand users’ personal preferences, we could rank the services in a more satisfactory way. Many users have some general preferences on the desired values of non-functional properties (e.g. provider history, service popularity, etc.) of services, even if they may not explicitly define them. In this paper, we propose to build user profiles on these non-functional preferences, and then use them to personalize the ranking results for individual users. Our experiment showed that personalized ranking could promote the services matching with the user preferred non-functional values to higher positions, making it easier for users to identify their desired services. We also tested how different factors impact the degree of improvement on the ranking accuracy.

Keywords

Service Ranking Service Selection Non-functional Preference User Modeling Personalization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Rozita Mirmotalebi
    • 1
  • Chen Ding
    • 1
  • Chi-Hung Chi
    • 2
    • 3
  1. 1.Department of Computer ScienceRyerson UniversityTorontoCanada
  2. 2.School of SoftwareTsinghua UniversityBeijingChina
  3. 3.Intelligent Sensing and Systems Laboratory – CSIROHobartAustralia

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