{"title":"CoNavigator: A Framework of FCA-Based Novel Coronavirus COVID-19 Domain Knowledge Navigation","authors":"F. Hao, D. Park","doi":"10.22967/hcis.2021.11.006","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":54258,"journal":{"name":"Human-Centric Computing and Information Sciences","volume":"11 1","pages":"12"},"PeriodicalIF":3.9000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human-Centric Computing and Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.22967/hcis.2021.11.006","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 10
Abstract
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.
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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