A Categorical Review of Recommender Systems

As more and more information became available electronically, the need for effective information retrieval and implementation of filtering tools have became essential for easy access of relevant information. Recommender Systems (RS) are software tools and techniques providing suggestions for items and/or services to be of use to a user. These systems are achieving widespread success in ecommerce applications now a days, with the advent of internet. This paper presents a categorical review of the field of recommender systems and describes the state-of-the-art of the recommendation methods that are usually classified into four categories: Content based Collaborative, Demographic and Hybrid systems. This paper discusses the pro’s and con’s of the current categories as well as the trustworthiness of the recommender system in a new dimension as evaluating the evaluator for more appropriate recommendations. In the domain of recommender system, this work also put forward the use of agents asan enabling technology.