Fuzzy Based Hybrid Mobile Recommendation System
Angira Amit Patel, Jyotindra N. Dharwa · 2016
The emergence of personalization in new generation e-commerce and power shift towards consumers enforces incorporation of recommendation system. To implement that, an innovative user web-interactions models and novel recommendation strategy will be in demand. This research work looks for innovative approach for on-line mobile trades, which integrate knowledge of expert with product specifications to develop hybrid personalized recommendations system. The uniqueness of this work includes advanced user-web interaction strategies, need based mobile selections criteria and added gain of expert knowledge. The very well known, fuzzy logic technique had implied to compute similarity matching along with flexibility. Experimental results demonstrate the competence test of system by getting feedback about customer satisfaction against various perspectives of systems performance. The proposed research work could also provide guidelines to deal with design challenge for personalized recommendations model for many other domains.