Comparison of collaborative and content-based automatic recommendation approaches in a digital library of Serbian PhD dissertations

Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/103260

Title:	Comparison of collaborative and content-based automatic recommendation approaches in a digital library of Serbian PhD dissertations
Authors:	Azzopardi, Joel Ivanovic, Dragan Kapitsaki, Georgia
Keywords:	Singular value decomposition Recommender systems (Information filtering) -- Serbia Digital libraries -- Serbia Electronic information resources -- Serbia Information storage and retrieval
Issue Date:	2016
Publisher:	Springer
Citation:	Azzopardi, J., Ivanovic, D., & Kapitsaki, G. (2016, September). Comparison of collaborative and content-based automatic recommendation approaches in a digital library of Serbian PhD dissertations. International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, Coimbra.
Abstract:	Digital libraries have become an excellent information resource for researchers. However, users of digital libraries would be served better by having the relevant items ‘pushed’ to them. In this research, we present various automatic recommendation systems to be used in a digital library of Serbian PhD Dissertations. We experiment with the use of Latent Semantic Analysis (LSA) in both content and collaborative recommendation approaches, and evaluate the use of different similarity functions. We find that the best results are obtained when using a collaborative approach that utilises LSA and Pearson similarity.
URI:	https://www.um.edu.mt/library/oar/handle/123456789/103260
Appears in Collections:	Scholarly Works - FacICTAI

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