Semantic Analysis of Big Data in Hierarchical Interpretation of Recommendation Systems

  • R. LavanyaEmail author
  • B. Bharathi
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 39)


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.


Big data User preferences Recommendation system Collaborative filtering Semantic analysis 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSathyabama Institute of Science and TechnologyChennaiIndia

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