Online Search and Recommendation in Consumer Market

Abstract: Recommender systems are one of the new- generation internet based tools that help users in navigating through information and receive information related to their purchase preferences. To overcome the information overload of internet-based shopping customers, we introduce a semantic recommendation based procedure which is more efficient and easier to use than available methods in the market. The suggested procedure based its recommendation of the products to the customer and is originally based on data mining techniques, like associate rule mining and frequent pattern mining. The novelty of our approach lies in providing the information of geographically nearby local markets to the users. Purchase recommendations will be also based on locality reference, and user�s purchase profile.

Keywords: Recommender System, (GSM) Global System for Mobile Communications, (GPS) Global Positioning System, ID3 (Iterative Dichotomiser 3), Machine learning, (NLP) Natural language processing.