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Name - Gaurav Jivan Sawale (19ENG7ECE0006)

Branch - Computer Science & Engineering

Faculty - Faculty of Engineering & Technology

Date of Registration - 21st October 2019

Supervisor - Dr. Manoj Kumar Rawat, Professor.

Date of Ph.D. Viva - 25th August 2023

Title - Automated Framework for Stock Market Prediction using Sentiment Analysis and Machine Learning Approach


1. Gaurav J.Sawale and Dr. Rakesh Sharma, “Investing approaches for Sentiment Analysis regarding even driven system data to predict the behaviour of Stock market: A Review”, presented at National Conference on Interdisciplinary Research and Innovative Technologies (NCIRIT 2020) at SAGE University, Indore and published in Wesleyan Journal of Research, Vol.14 No2(I), 2021.


2. Gaurav J.Sawale and Dr. Manoj K. Rawat,“ Stock Market Predication using Sentiment Analysis and Machine Learning Approach”, presented at International E-Conference on Emerging Trends & Latest Researches in Computer Science (SIC-ETRCS-2022) organised by IAC,ICA,SIRT , SAGE University ,Indore from 28th to 29th January 2022.


3. Gaurav J.Sawale and Dr. Manoj K. Rawat, “Stock Market Prediction using Sentiment Analysis and Machine Learning Approach”, presented at Forth International Conference on Smart Systems and Inventive Technology (ICSSIT 2022) organised by Francis Xavier Engineering College Tirunelveli , India from 20th to 22nd January 2022,and published in IEEE Xplore Compliant Number; ISBN: 978-1-6654-0018-0.


4. Gaurav J.Sawale and Dr. Manoj K. Rawat, “Stock Market Prediction using Sentiment Analysis ”, presented at International Conference on Recent Advances in Materials, Manufacturing and Machine Learning (RAMMML-2022) organised by “Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur from 26th to 27th April 2022.

  
5. Gaurav J. Sawale and Dr. Manoj K. Rawat, “Stock Market Forecasting Using Metaheuristic LSTM Approach with Sentiment Analysis”, Journal of Specialusis Ugdymas / Special Education 2022 2 (43), October 2022.



http://hdl.handle.net/10603/524065