Intelligent Information Management

Volume 8, Issue 2 (March 2016)

ISSN Print: 2160-5912   ISSN Online: 2160-5920

Google-based Impact Factor: 1.70  Citations  h5-index & Ranking

Incorporating User’s Preferences into Scholarly Publications Recommendation

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DOI: 10.4236/iim.2016.82004    2,308 Downloads   2,889 Views   Citations

ABSTRACT

Over the years, there has been increasing growth in academic digital libraries. It has therefore become overwhelming for researchers to determine important research materials. In most existing research works that consider scholarly paper recommendation, the researcher’s preference is left out. In this paper, therefore, Frequent Pattern (FP) Growth Algorithm is employed on potential papers generated from the researcher’s preferences to create a list of ranked papers based on citation features. The purpose is to provide a recommender system that is user oriented. A walk through algorithm is implemented to generate all possible frequent patterns from the FP-tree after which an output of ordered recommended papers combining subjective and objective factors of the researchers is produced. Experimental results with a scholarly paper recommendation dataset show that the proposed method is very promising, as it outperforms recommendation baselines as measured with nDCG and MRR.

Cite this paper

Igbe, T. and Ojokoh, B. (2016) Incorporating User’s Preferences into Scholarly Publications Recommendation. Intelligent Information Management, 8, 27-40. doi: 10.4236/iim.2016.82004.

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