Multimedia Tools and Applications

, Volume 74, Issue 24, pp 11399–11428 | Cite as

Towards context-sensitive collaborative media recommender system

  • Mohammed F. Alhamid
  • Majdi Rawashdeh
  • Hussein Al Osman
  • M. Shamim Hossain
  • Abdulmotaleb El Saddik
Article

Abstract

With the rapid increase of social media resources and services, Internet users are overwhelmed by the vast quantity of social media available. Most recommender systems personalize multimedia content to the users by analyzing two main dimensions of input: content (item), and user (consumer). In this study, we address the issue of how to improve the recommendation and the quality of the user experience by analyzing the contextual aspect of the users, at the time when they wish to consume multimedia content. Mainly, we highlight the potential of including a user’s biological signal and leveraging it within an adapted collaborative filtering algorithm. First, the proposed model utilizes existing online social networks by incorporating social tags and rating information in ways that personalize the search for content in a particular detected context. Second, we propose a recommendation algorithm to improve the user experience and satisfaction with the use of a biosignal in the recommendation process. Our experimental results show the feasibility of personalizing the recommendation according to the user’s context, and demonstrate some improvement on cold start situations where relatively little information is known about a user or an item.

Keywords

Personalized search Context media search Context-aware recommendation Collaborative context Retrieval model Information filtering 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Mohammed F. Alhamid
    • 1
    • 2
  • Majdi Rawashdeh
    • 3
  • Hussein Al Osman
    • 1
  • M. Shamim Hossain
    • 2
  • Abdulmotaleb El Saddik
    • 1
    • 2
  1. 1.Multimedia Communications Research Laboratory (MCRlab), School of Electrical Engineering and Computer ScienceUniversity of OttawaOttawaCanada
  2. 2.College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhSaudi Arabia
  3. 3.Division of EngineeringNew York University Abu DhabiAbu DhabiUnited Arab Emirates

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