A Novel Approach for Book Recommendation using Fuzzy based Aggregation

Objectives: To propose the top books for universities students by using the proposed fuzzy based approach, Ordered Ranked weighted Aggregation method. Methods/Statistical Analysis: The recommendations of books by different universities differ significantly. A staunch aggregation of the differently recommended books by the top ranked universities may lead to vigorous recommendation. We apply Positional Aggregation based Scoring technique, a rank aggregation method for partial list. We have suggested Ordered Ranked Weighted Aggregation (ORWA) operator, which assigns weights to the ranker. Findings: By using proposed technique, the recommendation of top ranked university is preferred over lower ranked universities. The philosophy of ORWA is the fact that the recommendation of a book by a top ranked university will eventually increase the importance of the recommended books. The top 20 books on "Artificial Intelligence" are recommended using PAS and ORWA based techniques. The recommendation would help the users in finding the books of their requirement. Improvements: The relative comparisons between both the discussed techniques PAS and ORWA are discussed and shown graphically. The results indicate a clear improvement of ORWA over PAS.