Survey of User to User Recommendation System in Online Social Networks | ||
| Engineering and Technology Journal | ||
| Article 7, Volume 37, 10A, October 2019, Pages 422-428 PDF (186.97 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.30684/etj.37.10A.7 | ||
| Authors | ||
| Sammer A. Qader; Ayad R. Abbas | ||
| Computer Sciences, University Of Technology - Iraq | ||
| Abstract | ||
| The widespread use of online social networks (OSN) and their applications by users lead to the lack of knowledge identification of their needs across the vast amount of data, which made the need to create systems that help people to solve the problems and make decisions with more accuracy, an example of these systems is the Recommendation system (RS), which helps users to make decision and save time in search on a commercial or personal level, one of the most critical types of recommendation systems is the friends recommendation system (FRS) . In this survey, several studies have been suggested to solve the problem of FRS and its mechanism, techniques, and algorithms used to create them Also, the RS types and techniques, a variety of dataset that deals with a specific system, are explained. Moreover, the challenges they face to determine the needs of people in terms of the choice of items or at the level of social networks are included. | ||
| Keywords | ||
| Recommendation System; Friends Recommendation System; Collaborative Filtering; Content-based Filtering; Social dataset | ||
| References | ||
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