A Study on Recommendation Categories in Academic D-library

Abstract

Users increasingly enjoy unprecedented access to varied and huge number of digital resources provided by the academic D-libraries to enrich their education and knowledge. As an academic digital libraries' contents become huger, it is difficult for users to obtain the needed information resources accurately and quickly. Thus, users expect more sophisticated services from digital library systems such as easy to retrieve relevant resources. One effective solution to handle this issue is to make use of recommendation service. The aim of this study is to investigate on the recommender system categories used in academic D-libraries. The paper review the most important categories including collaborative filtering, content filtering and hybrid filtering with their major strengths and limitations. Then, issues and challenges related to these categories are presented, followed by a discussion of solutions proposed by researchers to mitigate these challenges. Finally, based on the survey, a future research possibilities to develop high-quality recommender systems for academic D-libraries is presented.