Publication

Abstract : In this paper, we propose a novel method which establishes a newborn relation between Signal Processing and Natural Language Pro- cessing (NLP) method via Variational Mode Decomposition (VMD). Unlike the modern Neural Network approaches for NLP which are complex and often masked from the end user, our approach involving Term Fre- quency - Inverse Document Frequency (TF- IDF) aided with VMD dials down the com- plexity retaining the performance with trans- parency. The performance in terms of Ma- chine Learning based approaches and seman- tic relationships of words along with the methodology of the above mentioned ap- proach is analyzed and discussed in this paper.