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Covid-19 Vaccination Classification of Opinion Mining with Semantic Knowledge-based Decision Making
<!DOCTYPE html> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Covid-19 Vaccination Classification of Opinion Mining with Semantic Knowledge-based Decision Making</title> <!-- common meta tags --> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <meta http-equiv="X-UA-Compatible" content="ie=edge"> <meta name="title" content="Covid-19 Vaccination Classification of Opinion Mining with Semantic Knowledge-based Decision Making"> <meta name="description" content="The Covid-19 ontology is to classify the data using a supervised learning approach in machine learning, which has been preprocessed. Afterthe classification is done, with thehelp of opinion mining with decisionmaking, the classified data is stored in the database using semantic webontology using the prot茅g茅 tool. The data will be retrieved through SPARQL which helps to retrieve complex queries, followed by the output based on the given query. This Covid-19 ontology helps in analyzing the risk factors and treatment plans for the respective individuals i.e., students based on their given details which include diagnosis, symptoms, and vaccination history. The information given by the students can be automatically processed and with the help of SWRL (Semantic Web Rule Language), the risk factor and treatment plans for the students are inferred from the given knowledge"/> <meta name="keywords" content="Covid-19, SPARQL, Semantic Web, SWRL, Ontology"/> <!-- end common meta tags --> <!-- INDEX meta tags --> <meta name="google-site-verification" content="t8rHIcM8EfjIqfQzQ0IdYIiA9JxDD0uUZAitBCzsOIw" /> <meta name="yandex-verification" content="e3d2d5a32c7241f4" /> <!-- end INDEX meta tags --> <style type="text/css"> a{ color:white; text-decoration:none; } ul li a{ font-weight:bold; color:#000; list-style:none; text-decoration:none; size:10px;} .imagess { height:90px; text-align:left; margin:0px 5px 2px 8px; float:right; border:none; } #left p { font-family:CALIBRI; font-size:0.90pc; margin-left: 20px; } .right { margin-right: 20px; } #button{ float: left; font-size: 17px; margin-left: 10px; height: 28px; width: 100px; background-color: #1e86c6; } </style> <link rel="icon" type="image/ico" href="/favicon.ico"/> <link rel="stylesheet" type="text/css" href="../current.css" /> </head> <body> <div id="wap"> <div id="page"> <div id="top"> <table width="100%" cellspacing="0" cellpadding="0" > <tr><td colspan="3" valign="top"><img src="../ijwest.jpg" /></td></tr> </table> </div> <div id="menu"> <a href="http://www.airccse.org/journal/ijwest/ijwest.html">Home</a> <a href="http://www.airccse.org/journal/ijwest/editorialboard.html">Editorial</a> <a href="http://www.airccse.org/journal/ijwest/papersub.html">Submission</a> <a href="http://www.airccse.org/journal/ijwest/indexing.html">Indexing</a> <a href="http://www.airccse.org/journal/ijwest/specialissue.html">Special Issue</a> <a href="http://www.airccse.org/journal/ijwest/contact.html">Contacts</a> <a href="http://airccse.org" target="_blank">AIRCC</a></div> <div id="content"> <div id="left"> <h2>Volume 13, Number 3</h2> <h4 style="text-align:center;"><a>Covid-19 Vaccination Classification of Opinion Mining with Semantic Knowledge-based Decision Making</a></h4> <h3> Authors</h3> <p class="#left">Nikhila Polkampally, D. Rakesh Kumar, G. Soma Sekhar and Mettu Karuna Sri Reddy, Geethanjali College of Engineering and Technology, India </p> <h3> Abstract</h3> <p class="#left right" style="text-align:justify">The Covid-19 ontology is to classify the data using a supervised learning approach in machine learning, which has been preprocessed. Afterthe classification is done, with thehelp of opinion mining with decisionmaking, the classified data is stored in the database using semantic webontology using the prot茅g茅 tool. The data will be retrieved through SPARQL which helps to retrieve complex queries, followed by the output based on the given query. This Covid-19 ontology helps in analyzing the risk factors and treatment plans for the respective individuals i.e., students based on their given details which include diagnosis, symptoms, and vaccination history. The information given by the students can be automatically processed and with the help of SWRL (Semantic Web Rule Language), the risk factor and treatment plans for the students are inferred from the given knowledge. </p> <h3> Keywords</h3> <p class="#left right" style="text-align:justify">Covid-19, SPARQL, Semantic Web, SWRL, Ontology.</p> <br> <button type="button" id="button"><a target="blank" href="http://aircconline.com/ijwest/V13N3/13322ijwest01.pdf">Full Text</a></button> <button type="button" id="button"><a href="http://www.airccse.org/journal/ijwest/vol13.html">Volume 13</a></button> <br><br><br><br><br> </div> <div id="right"> <div class="menu_right"> <ul> <li><a href="http://www.airccse.org/journal/ijwest/archives.html">Archives</a></li> </ul> </div><br /> <p align="center"> </p> <p align="center"> </p> </div> <div class="clear"></div> <div id="footer"><table width="100%" ><tr><td height="25" colspan="2"><br /><p align="center">® All Rights Reserved - AIRCC</p></td></table> </div> </div> </div> </div> </body> </html>