A LITERATURE REVIEW AND CLASSIFICATION OF BOOK RECOMMENDATION RESEARCH - Feng Wang; Lingling Zhang; Xin Xu (JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM), 2020)
The act of reading has benefits for individuals and societies, which can be a long-term commitment. While the overload of books information and readers’ specific needs make book recommendation (BR) in demand, BR is receiving great attention from the research community with different perspectives. The increasing amount of research conducted with BR calls for a classification methodology regarding trends and distribution in this field. This paper presents a study of recommender systems in the domain of BR. The main goal of this work is to provide authors with insights on the trends of academic literature reviews in the proposed context and to present a comparison of different research approaches. The authors searched for up-to-date research papers related to recommender systems for BR within a time period of eighteen years, from 2000 to 2018. Starting from 2000, a significant amount of research related to the subject field of recommender systems was conducted, which led to the first ACM Conference on Recommender Systems. After the filtering process, 39 papers were finally selected from journals, conferences and theses in five different academic databases (i.e. IEEE, ACM, Science Direct, Springer and ProQuest). The general classification is presented in this work, in order to describe the recommendation approaches for BR. This work can be extended in the future to include novel methodologies and trends of recommender systems for BR or other fields.