Design and Implementation of Grievance Filing Application using Automatic Text Classification
Shradha Sawant1, Manjushree Shinde2, Samruddhi Siddhamshettiwar3, Nisha Watpade4, Jayashree Jagdale5
1Shradha Sawant*, Dept. of Information Technology, Pune Institute of Computer Technology (PICT), Pune, India.
2Manjushree Shinde, Dept. of Information Technology, Pune Institute of Computer Technology, Pune, India.
3Samruddhi Siddhamshettiwar, Dept. of Information Technology, Pune Institute of Computer Technology, Pune, India.
4Nisha Watpade, Information Technology, Pune Institute of Computer Technology, Pune, India.
5Jayashree Jagdale, Assistant Professor, Dept. of Information Technology, Pune Institute of Computer Technology, Pune.
Manuscript received on April 20, 2020. | Revised Manuscript received on May 01, 2020. | Manuscript published on May 10, 2020. | PP: 1332-1336 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5852059720/2020©BEIESP | DOI: 10.35940/ijitee.G5852.059720
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This research aims to design a Grievance Filing System built using automatic text classification without any manual interruption. Various methodologies are followed to achieve it and are implemented. Performance of the different algorithms is discussed. People are less aware about the lengthy methods for lodging complaints. We propose a simplified process of enrolling grievances to ministries. The system accepts grievances in recorded voice form. The system is designed for Marathi language. Input in the form of speech will ease people’s comfort for lodging grievances. We present a model where voice is first preprocessed, followed by text classification using deep learning approaches such as CNN and LSTM, the grievances will be sent to respective ministry. This system can be used by government ministries to get grievances from common people through a simplified process. User will be notified on the progress of their lodged complaint and on its successful resolution by respective ministry.
Keywords: Deep Learning, LSTM, CNN, Text Classification.
Scope of the Article: Classification