An improved memory-based collaborative filtering method based on the TOPSIS technique.

ABSTRACT: This paper describes an approach for improving the accuracy of memory-based collaborative filtering, based on the technique for order of preference by similarity to ideal solution (TOPSIS) method. Recommender systems are used to filter the huge amount of data available online based on user-defined preferences. Collaborative filtering (CF) is a commonly used recommendation approach that generates recommendations based on correlations among user preferences. Although several enhancements have increased the accuracy of memory-based CF through the development of improved similarity measures for finding successful neighbors, there has been less investigation into prediction score methods, in which rating/preference scores are assigned to items that have not yet been selected by a user. A TOPSIS

SUBMITTER: Al-Bashiri H 

PROVIDER: S-EPMC6171847 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature