Public opinion mining using natural language processing technique for improvisation towards smart city
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Public opinion mining using natural language processing technique for improvisation towards smart city S. Leelavathy1 · M. Nithya2 Received: 25 February 2020 / Accepted: 29 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In this digital world integrating smart city concepts, there is a tremendous scope and need for e-governance applications. Now people analyze the opinion of others before purchasing any product, hotel booking, stepping onto restaurants etc. and the respective user share their experience as a feedback towards the service. But there is no e-governance platform to obtain public opinion grievances towards covid19, government new laws, policies etc. With the growing availability and emergence of opinion rich information’s, new opportunities and challenges might arise in developing a technology for mining the huge set of public messages, opinions and alert the respective departments to take necessary actions and also nearby ambulances if its related to covid-19. To overcome this pandemic situation a natural language processing based efficient e-governance platform is demandful to detect the corona positive patients and provide transparency on the covid count and also alert the respective health ministry and nearby ambulance based on the user voice inputs. To convert the public voice messages into text, we used Hidden Markov Models (HMMs). To identify respective government department responsible for the respective user voice input, we perform pre-processing, part of speech, unigram, bigram, trigram analysis and fuzzy logic (machine learning technique). After identifying the responsible department, we perform 2 methods, (1) Automatic alert e-mail and message to the government departmental officials and nearby ambulance or covid camp if the user input is related to covis19. (2) Ticketing system for public and government officials monitoring. For experimental results, we used Java based web and mobile application to execute the proposed methodology. Integration of HMM, Fuzzy logic provides promising results. Keywords Speech processing · Hidden Markov models · Fuzzy logic · Natural language processing · Covid 19
1 Introduction Human voice based audio signals can be utilized by the doctors in detecting disease at the early stage and provide diagnosis. In existing systems the audio signals from the public are obtained in person manually by the doctors during the
* S. Leelavathy [email protected] M. Nithya [email protected] 1
Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions Research Foundation (Deemed to be University), Paiyanoor, India
Department of Computer Science and Engineering, Vinayaka Mission’s Kirupananda Variyar Engineering College, Vinayaka Missions Research Foundation (Deemed to be University), Salem, India
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consultant visits. In this pandemic situation smart device based voice analysis can be used for covid detection using trained dataset model (Pramono et al. 2017). In previ
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