基于语义知识决策的Covid-19疫苗分类意见挖掘

Nikhil Polkampally, D. Kumar, G. Sekhar, Mettu Karuna Sri Reddy
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引用次数: 0

摘要

Covid-19本体是使用机器学习中的监督学习方法对经过预处理的数据进行分类。分类完成后,利用意见挖掘与决策相结合的方法,利用语义网络本体将分类后的数据存储到数据库中。数据将通过SPARQL检索,SPARQL有助于检索复杂查询,然后是基于给定查询的输出。这个Covid-19本体有助于分析每个个体(即学生)的风险因素和治疗计划,这些个体基于他们的特定细节,包括诊断、症状和疫苗接种史。学生提供的信息可以自动处理,并借助语义网规则语言(SWRL),从给定的知识中推断出学生的风险因素和治疗方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Covid-19 Vaccination Classification of Opinion Mining with Semantic Knowledge-based Decision Making
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 protégé 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.
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