Experimental results for considering Item Adoption Eagerness Information in Collaborative Filtering’s Rating Prediction

TitleExperimental results for considering Item Adoption Eagerness Information in Collaborative Filtering’s Rating Prediction
Publication Typetechreport
Year of Publication2019
AuthorsMargaris D, Spiliotopoulos D, Vassilakis C
Date Published07/2019
PublisherSoftware and Database Systems Lab, University of the Peloponnese
Place PublishedTripolis
Type of WorkTechnical report
AbstractIn this technical report, we present the experimental findings from applying an algorithm that considers Item Adoption Eagerness Information in the rating prediction formulation process, in order to increase rating prediction quality in Collaborative Filtering (CF). To this end, the algorithm is applied to seven datasets, which are widely used in recommender system (RS) research. The results indicate that the above algorithm introduces considerable prediction accuracy gains.
URLhttps://soda.dit.uop.gr/?q=TR-19003
Citation KeySODA-TR-19003
Full Text