DESIGN AND ANALYSIS OF A NOVEL HYBRID RECOMMENDER SYSTEM FOR EFFICIENT MAP ROUTING BASED ON USER PREFERENCES

In the past few years, with the proliferation of mobile devices people are experiencing frequent communication and information exchange. For instance, in the context of people's visits, it is often the case that each person carries out a smart phone, to get information about nearby places. When one visits some location, an application will recommend useful information according to its current location, preferences and past visits. This paper introduces the concept of smart routing as a recommender system for tourists that takes into account the dynamics of their personal user profiles. The concept relies on the hybrid recommender system for map routing which can be used as the alternative to the current systems. This system implements hybridization of content and collaborative-filtering. The purpose of this paper is to build a system for web and mobile based applications with the idea of recommending parameters like food, restaurants, hospitals, ATMs etc. according to users' current location, preferences and past visits. This approach has its roots in information filtering and retrieval research. The proposed system has also taken care of the cold start problem for new users.