Recommender System Based on User Functional Requirements Using Euclidean Fuzzy

Recommender System Based on User Functional Requirements Using Euclidean Fuzzy

Author		: KEN ARNETT DS; Z K ABDURAHMAN BAIZAL; ADIWIJAYA
Published on	: The 3rd International Conference of Information and Communication Technology 2015 (ICoICT 2015)

Abstract

Customer often feels difficult to describe what he needs when he intends to buy a high-tech product with complex features, like smartphone, notebook, camera, PC, car, server, etc. It is because the most of users are less familiar with the technical features of this product types. However, most recommender systems had been developed still directly refer to product features when gathering user???s requirement. Naturally, users often express their needs based on their functional requirements (need smartphone for gaming, reading e-book, online activity, etc). Considering the problems, this paper propose an new approach for functional-based recommendation computation in recommender system, with more properly product recommendations. The computation uses mapping concept towards functional requirements including their supporting features, components product (technical details of features) as well as Euclidean Fuzzy for calculating the similarity. The domain of our recommendation system is Smartphone area. The test of the approach shows that the computation was accurate for 92.67%.