Collaborative Filtering: Data Sparsity Challenges

Abstract

Today internet is a place where the huge amount of data is stored, there is need to sift, which create a problem for the internet user, so recommend system solve the problem. A recommendation system is a system that helps a user found the products and content by forecast the user’s rating of each item and showing them the items that they would rate highly. Recommendation systems are everywhere. With online shopping, customer has nearly infinite choices. No one has enough time to try every product for sale. Recommendation systems play an important role to solve the users search the products and content they care about. Recommendation system is a process of filtering the information that deal with information overloaded problems. Recommendation system is important for both user and service provider. It reduces the cost of transaction and selecting item in an online scenario it also improves the quality of decision-making process. It is now an effective means for selling their product. So over emphasized of user is not good for recommendation system. To solve the problems of recommendation system like data sparsity we use one of best technique that is collaborative filtering technique.