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A Multidimensional Paper Recommender: Experiments and Evaluations

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2 Author(s)
Tang, T.Y. ; Konkuk Univ., Seoul, South Korea ; McCalla, G.

Paper recommender systems in the e-learning domain must consider pedagogical factors, such as a paper's overall popularity and learner background knowledge - factors that are less important in commercial book or movie recommender systems. This article reports evaluations of a 6D paper recommender. Experimental results from a human subject study of learner preferences suggest that pedagogical factors help to overcome a serious cold-start problem (not having enough papers or learners to start the recommender system) and help the system more appropriately support users as they learn.

Published in:

Internet Computing, IEEE  (Volume:13 ,  Issue: 4 )