Recommendation system for under graduate students using FSES-TOPSIS

Abstract

Existing recommendation systems lack to address the need of several problems in education domain due to the availability of limited information. Study of recommendation systems to facilitate students' education in their relevant services is being carried out in different perspective. Hence, the objective of this work is to apply existing knowledge for decision making to recommend students during their course registration process in an institution. The situation where more number of experts involves in decision making was influenced by Fuzzy Soft Expert Set (FSES). This work emphasizes the application of FSES for facilitating students' course registration process assuming that the same course is offered by more number of faculty members during a semester. As more number of experts involved in this process and the uncertainty of the available data, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) along with FSES was considered. A new methodology FSES-TOPSIS was also applied in this work. The proposed method was accurate enough to enable students to rank the faculty members based on their previous performance and to enroll themselves with the faculty members of their interest. The method proposed here can be extended for various problems of similar nature.