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Sentimental Analysis Using Convolution Neutral Network Through Word to Vector Embedding for Patients Dataset

  • G. ParthasarathyEmail author
  • D. Preethi
  • Mary Subaja Christo
  • T. R. Soumya
  • J. Saravanakumar
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)

Abstract

Sentimental analysis involves the incorporation of working of a structure that explores sentiments seen in blog sections, comments, or tweet relating to a thing or point. In this proposed research, the authors have used speech recognition for collecting the opinions from patients relating to health care. The mental condition of a patient in respect of the health care has been identified through sentimental analysis based on the convolutional neural network using some convolutional filter (1D) in word2vec logistic synopsis. It features implicit or explicit determination of the patient’s strength based on sentiments through results. It helps the physician in taking necessary action. Accuracy of the result is of help in the recommendation to the patient by the physicians and health care centers.

Keywords

Audio Speech recognition Opinion Sentimental mining Convolutional neural network Word to vector (w2v) 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • G. Parthasarathy
    • 1
    Email author
  • D. Preethi
    • 2
  • Mary Subaja Christo
    • 3
  • T. R. Soumya
    • 2
  • J. Saravanakumar
    • 2
  1. 1.Department of Computer Science and Engineering, Jeppiaar Maamallan Engineering CollegeAnna UniversityChennaiIndia
  2. 2.Saveetha School of EngineeringThandalamIndia
  3. 3.School of C&ITREVA UniversityBengaluruIndia

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