导航器:基于fca的新型冠状病毒COVID-19领域知识导航框架

IF 3.9 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Human-Centric Computing and Information Sciences Pub Date : 2021-01-01 DOI:10.22967/hcis.2021.11.006
F. Hao, D. Park
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引用次数: 10

摘要

新型冠状病毒病(COVID-19)大流行的确诊病例数量迅速增加,医疗资源极其丰富,正在丰富COVID-19领域知识库。这无疑给用户带来了“信息超载”和“信息混乱”。因此,如何实现COVID-19相关领域知识检索和个性化服务的精准信息导航,成为本研究的巨大挑战。由于概念格独特的检索和导航优势,基于形式概念分析(FCA)理论设计了新型冠状病毒COVID-19领域知识导航框架connavigator。为提高各种新型冠状病毒信息资源平台的检索效率提供了一种有前景的途径。此外,我们还提取了一些有用的模式,作为正确理解新型冠状病毒COVID-19病理特征的重要证据。
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CoNavigator: A Framework of FCA-Based Novel Coronavirus COVID-19 Domain Knowledge Navigation
The rapidly increasing number of confirmed cases and extremely large amounts of medical resources about coronavirus disease 2019 (COVID-19) pandemic are enriching the COVID-19 domain knowledge bases. Undoubtedly, it is resulting in "information overload" and "information confusion" for users. Hence, how to achieve precision information navigation for COVID-19 related domain knowledge retrieval and personalized services, has become a huge challenge of this research. Due to the unique retrieval and navigation advantages of concept lattice, a framework of novel coronavirus COVID-19 domain knowledge navigation named CoNavigator, based on Formal Concept Analysis (FCA) theory is devised. It provides a promising approach for improving the retrieval efficiency from various novel coronavirus COVID-19 information resource platforms. Besides, some useful patterns are extracted and regarded as important evidence for an appropriate understanding of the pathological features of novel coronavirus COVID-19.
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来源期刊
Human-Centric Computing and Information Sciences
Human-Centric Computing and Information Sciences Computer Science-General Computer Science
CiteScore
13.10
自引率
12.10%
发文量
0
审稿时长
13 weeks
期刊介绍: In Human-centric Computing and Information Sciences (HCIS), KIPS-CSWRG publishes high quality papers which cover the various theories and practical applications related to human-centric computing and information sciences. The published papers present results of significant value to solve the various problems with application services and other problems which are within the scope of HCIS. In addition, we expect they will trigger further related research and technological improvements relevant to our future lives.
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