Semantic analysis of big data in hierarchical interpretation of recommendation systems

Abstract

In today’s scenario where Big Data is being used at its maximum potential, showing most of its influence on searching from the internet. It gives out large amount of data to the user which becomes too overwhelming for the user to analyze and understand. This led to the introduction of Recommendation Systems whose main purpose is to give relevant datasets according to the user’s preference which makes it easy for the user to understand and analyze the best option among the limited options he/she has received from the system. Recommendation Systems exhibit some kind of implicit hierarchy based on either users or items to give the best recommendation to users. But it has been noticed that these systems produce a lot of ambiguities. Hence, leading to a lot of repeated results. This paper investigate various ways to understand the implicit working of hierarchical structures and make some improvisations on the same with the help of semantic analysis under collaborative filtering approach.