A Fuzzy Approach to Multidimensional Context Aware e-Learning Recommender System

  • Pragya Dwivedi
  • Kamal K. Bharadwaj
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8284)


Traditional e-Learning recommender systems (EL-RS) based on two dimensions- learners and learning resources, help learners in alleviating information overload by providing suitable learning resources from a potentially overwhelming variety of choices. E-learning recommender systems have received considerable attention in recent years. However, the incorporation of contextual information such as time duration and mood of a learner into the e-Learning recommendation process is still in its infancy. Such contextualization is investigated as an exemplar for EL-RS that can anticipate the learners’ requirements. Usually, the representation of learner context is subjective, imprecise and vague. In this paper, we propose a fuzzy approach to multidimensional context aware EL-RS (CA-EL-RS) that includes time duration and mood of a learner as additional dimensions for item based collaborative filtering (IB-CF). The empirical results are presented to demonstrate the effectiveness of the proposed approach in identifying better top N recommendations than traditional IB-CF.


e-Learning Multidimensional Recommender Systems Context-Aware Recommender Systems Item-based Collaborative Filtering 


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Pragya Dwivedi
    • 1
  • Kamal K. Bharadwaj
    • 2
  1. 1.Computer Science & Engineering DepartmentMotilal Nehru National Institute of TechnologyAllahabadIndia
  2. 2.School of Computer and Systems SciencesJawaharlal Nehru UniversityNew DelhiIndia

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