Ordered ranked weighted aggregation based book recommendation technique: A link mining approach

The intense growth of the modern technologies has caused data overload over the Internet. The increasing data over the World Wide Web has created the problems for the users to extract the exact information. The growth of the Internet has also boosted the e-commerce. The popularity of online shopping has grown up rapidly. Online shopping has become much more popular. While browsing the e-marketing portals, multiple options are presented before users; hence picking the right item is a difficult job. In this paper we propose a recommendation method for books. We have adopted link mining approach to recommend books using Ordered Ranked Weighted Averaging (ORWA) aggregation operator. ORWA is a modified form of Ordered Weighted Aggregated averaging (OWA) operator, a multi criteria decision making procedure. The weight generation using guided quantifier does not take into account the value of the voters, here, rankers which recommend the products, i.e. universities' ranking. Therefore the top ranked universities are considered and their recommended books are listed. We propose an algorithm to score the ranked books. By applying ORWA operator, best ranked books are recommended. This method may fulfill the requirement of the millions of students and academician who seek for their desired books.