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Multi-method Evaluation in Scientific Paper Recommender Systems

  • User Modeling, Adaptation, and Personalization
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Abstract

Recommendation techniques in scientific paper recommender systems (SPRS) have been generally evaluated in an offline setting, without much user involvement. Nonetheless, user relevance of recommended papers is equally important as system relevance. In this paper, we present a scientific paper recommender system (SPRS) prototype which was subject to both offline and user evaluations. The lessons learnt from the evaluation studies are described. In addition, the challenges and open questions for multi-method evaluation in SPRS are presented.

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Publication details

DOI
10.1145/3213586.3226215
Semantic Scholar
aab1ed06e51a09843ce7d489bffe49ff61eee258
Document type
Book
Source
User Modeling, Adaptation, and Personalization
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