A Multi-Dimensional Paper Recommender

Frontiers in Artificial Intelligence and Applications

Volumn 158, Issue , 2007, Pages 653-655

  Tang, Tiffany Y ^a,b   McCalla, Gordon ^a  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

E - LEARNING; HUMAN SUBJECTS; MULTI DIMENSIONAL; PAPER RECOMMENDATIONS; PEDAGOGICAL FEATURES;

EID: 67249090483     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (11)

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3. Herlocker, J., Konstan, J, Terveen, L. and Riedl, J. Evaluating collaborative filtering recommender systems. ACM TOIS. Vol.22, no. 1, 5-53, January 2004.
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7. Pazzani, M. A Framework for collaborative, content-based, and demographic filtering. Artificial Intelligence Rev., 393-408, Dec. 1999.
8. Recker, M., Walker, A. and Lawless K. What do you recommend? Implementation and analyses of collaborative information filtering of web resources for education.Instructional Science 31:299-316. 2003.
9. Tang, T. Y., and McCalla, G. I. Utilizing artificial learners to help overcome the cold-start problem in a pedagogically-oriented paper recommendation system. AH 2004: 245-254
10. Tang, T. Y., and McCalla, G.I. Paper annotations with learner models. AIED 2005: 654-661.
11. Torres, R., McNee, S., Abel, M., Konstan, J.A. and Riedl, J. Enhancing digital libraries with TechLens. JCDL’04, 2004. 228-236.