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10.1007/s10772-020-09766-z http://scihub22266oqcxt.onion/10.1007/s10772-020-09766-z 33199973!7656096!33199973     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33199973&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Int+J+Speech+Technol 2021 ; 24 (3): 561-569 Nephropedia Template TP {{tp|p=33199973|t=2021. Public opinion mining using natural language processing technique for improvisation towards smart city |pdf=|usr=}}{{33199973}} gab.com Text Public opinion mining using natural language processing technique for improvisation towards smart city JO: Int J Speech Technol http://www.kidney.de/pget.php?&tw=1&pmid=33199973 #FOAvip 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. Twit Text FOAVip Public opinion mining using natural language processing technique for improvisation towards smart city ????Int J Speech Technol http://www.kidney.de/pget.php?&tw=1&pmid=33199973 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33199973 #FOAvip English Wikipedia <ref>{{Cite pmid|33199973}}</ref> Public opinion mining using natural language processing technique for improvisation towards smart city #MMPMID33199973 Leelavathy S; Nithya M Int J Speech Technol 2021[]; 24 (3): 561-569 PMID33199973show ga 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. ?Public opinion mining using natural language processing technique for (epmc).pdf DeepDyve Pubget Overpricing