|Title||Experimental results for considering Item Adoption Eagerness Information in Collaborative Filtering’s Rating Prediction |
|Publication Type||techreport |
|Year of Publication||2019 |
|Authors||Margaris D, Spiliotopoulos D, Vassilakis C |
|Date Published||07/2019 |
|Publisher||Software and Database Systems Lab, University of the Peloponnese |
|Place Published||Tripolis |
|Type of Work||Technical report |
|Abstract||In 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.
|Citation Key||SODA-TR-19003 |
|Full Text|| |