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Improved Model for Multiple Intent Processing
  • Chithra Apoorva DA,
  • Brahmananda S
Chithra Apoorva DA
GITAM

Corresponding Author:[email protected]

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Brahmananda S
GITAM
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Abstract

Natural language processing (NLP) is one among most researched topic Today. Usage of Neural Net model and other Machine learning improved model are gaining traction for solving complex single/Multi feature classification problem. Very often it has been observed that user utterances have many topics/intents, which carefully have to be identified and also do right entity mapping. In this direction various researches have been conducted and with time NLP models are well trained and coded. The goal of the paper is to improve the existing systems. We have identified a gap where “alarming situations” are being late handled either or it is being ignored. Therefore we are designing a system to improve performance as Better Accuracy, Finetuning of existing Model, Reduce Time complexity by invoking Asynchronous Method for parallel processing of tasks.