Review of Recommender Systems and Their Applications

In the past few decades, the concepts of personalization in the forms of recommender system, information filtering, or customization are not only quickly becoming more accepted by the public, but is also drawing considerable attention from enterprises. Therefore, a number of studies based on personalized recommendations have subsequently been produced. Most of these studies apply to E-commerce, website, and information, and some apply to teaching, tourism, and TV programs. Because of the recent rise of Web 3.0 and emphasis on providing more complete personal information and service through an efficient method, the recommender application has gradually developed towards mobile commerce, mobile information, or social network. Many studies have adopted Content- Based (CB), Collaborative Filtering (CF), and the hybrid approach as the main recommender style in the analysis. There are few or even no studies that have emphasized on the review of recommendations. For this reason, this study aims to collect, analyze, and review the research topics of recommender systems and their application in the past few decades. This study collects the research types from various researchers. The literature arrangement of this study can help researchers to understand the recommender system researches in a clear sense and in a short time.