AN OPTIMIZED RECOMMENDER SYSTEM WITH ENHANCED HYBRID FILTERING APPROACH

Abstract

The tremendous development of computer and internet technology has really changed the life of human in most of the aspects. Internet has change the way in which information used to be processed earlier, it has not only provided as excellent way for information flow but provided new platform for social networking, business, entertainment etc. On internet now companies can market as well as sell their products that have revolutionized the way business has done earlier. It saves a lot human effort and processing time, but the problems is how to search the relevant data from the large bulk of data which is present on the internet. The solution is the recommender system, they are the software solution used by most of the web sites, they search the all the data and apply some forms of pre and post filtering, and then provide more relevant results to the user by eliminating the irreverent data. But after the drastic popularity of smart phone and as the number of smart phone users raised up to 1.6 billion, now there is a need to develop better recommender system using more enhanced filtering approaches which are based on attributes like personal factors, current location of the user and mobile usage pattern of the user which are called psychographic factors.