Content-Based Knowledge Quality Assessment and Its Application in Health Management System

doi:10.1007/s12204-021-2266-8

摘要/Abstract

摘要： The growing demand for health management puts forward high requirements for the quality of health knowledge. A content-based method is proposed to address the current demand for high-quality health knowledge, which evaluates the quality including the certainty, accuracy, and operability of different types of knowledge from the perspectives of authority, precision, and information entropy. Herein, the health knowledge of myocardial infarction is used as an example, and knowledge is first classified into different types and then evaluated. This method is applied to knowledge in the existing health management system and it can support knowledge screening and comparison under the cold start condition. Compared with the current evaluation methods based on knowledge use behavior and utility, the new evaluation method provides a reference for evaluation when the knowledge is first used. The screening of high quality knowledge can help the subsequent application of knowledge and improve user’s compliance. Concurrently, the arrangement of myocardial infarction knowledge can also provide a knowledge reference for patients’ daily health management.

关键词: knowledge quality assessment, knowledge management, health management system, myocardial
infarction

Abstract: The growing demand for health management puts forward high requirements for the quality of health knowledge. A content-based method is proposed to address the current demand for high-quality health knowledge, which evaluates the quality including the certainty, accuracy, and operability of different types of knowledge from the perspectives of authority, precision, and information entropy. Herein, the health knowledge of myocardial infarction is used as an example, and knowledge is first classified into different types and then evaluated. This method is applied to knowledge in the existing health management system and it can support knowledge screening and comparison under the cold start condition. Compared with the current evaluation methods based on knowledge use behavior and utility, the new evaluation method provides a reference for evaluation when the knowledge is first used. The screening of high quality knowledge can help the subsequent application of knowledge and improve user’s compliance. Concurrently, the arrangement of myocardial infarction knowledge can also provide a knowledge reference for patients’ daily health management.

Key words: knowledge quality assessment, knowledge management, health management system, myocardial
infarction

中图分类号:

C 931.6

XIANG Yidan (项益丹), ZHANG Pengzhu (张朋柱), WU Shuang (吴双). Content-Based Knowledge Quality Assessment and Its Application in Health Management System[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(1): 116-128.

参考文献 51

[1]	BARRETT C. Pew Internet and American life project[M]//GELLMAN M D, TURNER J R. Encyclopediaof behavioral medicine. New York, USA: Springer,2013: 1464-1465.
[2]	DIAZ J A, GRIFFITH R A, NG J J, et al. Patients’use of the Internet for medical information [J]. Journalof General Internal Medicine, 2002, 17(3): 180-185.
[3]	WANG B. Research on credibility of medical informationbased on web analysis algorithm [D]. Mianyang,China: Southwest University of Science and Technology,2017 (in Chinese).
[4]	EYSENBACH G, POWELL J, KUSS O, et al. Empiricalstudies assessing the quality of health informationfor consumers on the World Wide Web: A systematicreview [J]. Journal of the American Medical Association,2002, 287(20): 2691-2700.
[5]	FAHY E, HARDIKAR R, FOX A, et al. Quality of patienthealth information on the Internet: Reviewing acomplex and evolving landscape [J]. Australasian MedicalJournal, 2014, 7(1): 24-28.
[6]	JIANG L H, WANG W. Medical knowledge-base andmedical knowledge acquirement [J]. Medical Information,2006, 19(9): 1500-1502 (in Chinese).
[7]	BYAMBASUREN O, YANG Y F, SUI Z F, et al. Preliminarystudy on the construction of Chinese medicalknowledge graph [J]. Journal of Chinese InformationProcessing, 2019, 33(10): 1-9 (in Chinese).
[8]	YUAN K Q, DENG Y, CHEN D Y, et al. Constructiontechniques and research development of medicalknowledge graph [J]. Application Research of Computers,2018, 35(7): 1929-1936 (in Chinese).
[9]	ZHENG Y M, ZHAI J, HU X L, et al. IntelligentQ&A and drug recommendation system based on TCMknowledge map [J]. Electronic Technology & SoftwareEngineering, 2019 (20): 134-135 (in Chinese).
[10]	L¨U Y J. Research on text mining in online health community[D]. Shanghai, China: Shanghai Jiao Tong University,2013 (in Chinese).
[11]	QU A Z, ZHUANG T G. The research of data miningand knowledge discovery in computer aided medical diagnosingsystem [J]. Foreign Medical Sciences BiomedicalEngineering, 2002, 25(3): 97-103 (in Chinese).
[12]	OU Z H. Knowledge management and knowledge evaluation[J]. Document, Information & Knowledge, 2006(3): 100-103 (in Chinese).
[13]	HE Y S, LI Y D. Knowledge management and medicalknowledge management system [J]. Chinese Hospitals,2001, 5(4): 51-53 (in Chinese).
[14]	HOU X R, CHEN J Y, ZHAO W L. Quality analysisof public medical and health information on the internet[J]. Chinese Journal of Health Informatics andManagement, 2014, 11(1): 38-42 (in Chinese).
[15]	ROTHROCK S G, ROTHROCK A N, SWETLAND S B, et al. Quality, trustworthiness, readability, and accuracyof medical information regarding common pediatricemergency medicine-related complaints on theWeb [J]. The Journal of Emergency Medicine, 2019,57(4): 469-477.
[16]	CHAROW R, SNOW M, FATHIMA S, et al. Evaluationof the scope, quality, and health literacy demandof Internet-based anal cancer information [J]. Journalof the Medical Library Association, 2019, 107(4): 527-537.
[17]	ALSHEHRI M G, JOURY A U. Quality, readability,and understandability of Internet-based informationon cataract [J]. Health and Technology, 2019, 9: 791-795.
[18]	RANADE A S, BELTHUR M V, OKA G A, et al.YouTube as an information source for clubfoot: Aquality analysis of video content [J]. Journal of PediatricOrthopedics B, 2020, 29(4): 375-378.
[19]	XIA Z F, GU K, WANG S Q, et al. Toward accuratequality estimation of screen content pictures with verysparse reference information [J]. IEEE Transactions onIndustrial Electronics, 2020, 67(3): 2251-2261.
[20]	LE C Y, GU X J. Enterprise knowledge automaticevaluation method based on user bahavior analysis [J].Computer Integrated Manufacturing Systems, 2015,21(5): 1368-1374 (in Chinese).
[21]	FIRESTONE J M, MCELROY M W. Introduction:What is the new knowledge management (TNKM),and what are its key issues? [M]// Key issuesin the new knowledge management. Boston, USA:Butterworth-Heinemann, 2003.
[22]	LE C Y, XU F Y, GU X J, et al. Evaluation modeland algorithm for knowledge contribution of enterprisestaff [J]. Computer Integrated Manufacturing Systems,2011, 17(3): 662-671 (in Chinese).
[23]	WEN T X. Study on knowledge kmeasurement andknowledge evaluation [J]. Evaluation & Management,2007, 5(1): 70-75 (in Chinese).
[24]	MCELROY M W. The new knowledge management[M]. Boston, USA: Butterworth-Heinemann, 2003: 3-32.
[25]	DENG S L, ZHAO H P. Quality evaluation of foreignnetwork health information: A review of indicators,tools and results [J]. Information and DocumentationServices, 2017 (1): 67-74 (in Chinese).
[26]	MARCINKOW A, PARKHOMCHIK P, SCHMODEA, et al. The quality of information on combined oralcontraceptives available on the Internet [J]. Journalof Obstetrics and Gynaecology Canada, 2019, 41(11):1599-1607.
[27]	BAI X Y, ZHANG Y W, LI J, et al. Online informationon Crohn’s disease in Chinese: An evaluationof its quality and readability [J]. Journal of DigestiveDiseases, 2019, 20: 596-601.
[28]	RAPTIS D A, SINANYAN M, GHANI S, et al. Qualityassessment of patient information on the managementof gallstone disease in the internet: A systematicanalysis using the modified ensuring quality informationfor patients tool [J]. HPB: The Official Journalof the International Hepato Pancreato Biliary Association,2019, 21(12): 1632-1640.
[29]	TAVARE A N, ALSAFI A, HAMADY M S. Analysisof the quality of information obtained about uterineartery embolization from the Internet [J]. CardioVascularand Interventional Radiology, 2012, 35: 1355-1362.
[30]	BURKE E, HARKINS P, SAEED M, et al. “Dr.Google” will see you now—assessing the quality of informationon oesophageal cancer on the internet [J].Journal of Gastrointestinal Surgery, 2020, 24: 2466-2470.
[31]	DENG S L, ZHAO H P. Research on the standardframework of the quality and the content evaluation ofonline health information from users’ perspective [J].Library and Information Service, 2017, 61(21): 30-39(in Chinese).
[32]	BLUMENSTOCK J E. Size matters: Word count asa measure of quality on Wikipedia [C]//Proceedingsof the 17th International Conference on World WideWeb. Beijing, China: ACM, 2008: 1095-1096.
[33]	WILKINSON D, HUBERMAN B. Cooperation andquality in Wikipedia [C]//Proceedings of the 2007 InternationalSymposium on Wikis. New York, USA:ACM, 2007: 157-164.
[34]	ADLER B T, DE ALFARO L. A content-driven reputationsystem for the Wikipedia [C]//Proceedingsof the 16th International Conference on World WideWeb. Banff, Alberta, Canada: ACM, 2007: 261-270.
[35]	HU M Q, LIM E P, SUN A X, et al. Measuringarticle quality in Wikipedia: Models and evaluation[C]//Proceedings of the 16th ACM Conference on Conferenceon Information and Knowledge Management.Lisbon, Portugal: ACM, 2007: 243-252.
[36]	W¨O HNER T, PETERS R. Assessing the qualityof Wikipedia articles with lifecycle based metrics[C]//Proceedings of the 5th International Symposiumon Wikis and Open Collaboration. Orlando, Florida,USA: ACM, 2009: 1-10.
[37]	BIANCANI S. Measuring the quality of edits toWikipedia [C]//Proceedings of The International Symposiumon Open Collaboration. Berlin, Germany:ACM, 2014: 1-3.
[38]	LI X Y, TANG J T, WANG T, et al. Automatically assessingWikipedia article quality by exploiting articleeditornetworks [C]//Proceedings of the 37th EuropeanConference on IR Research. Vienna, Austria: Springer,2015: 574-580.
[39]	SUZUKI Y. Quality assessment of Wikipedia articlesusing h-index [J]. Journal of Information Processing,2015, 23(1): 22-30.
[40]	SUZUKI Y, YOSHIKAWA M. Assessing quality scoreof Wikipedia article using mutual evaluation of editorsand texts [C]//Proceedings of the 22nd ACM InternationalConference on Information & Knowledge Management.San Francisco, California, USA: ACM, 2013:1727-1732.
[41]	DE LA ROBERTIE B, PITARCH Y, TESTE O. Measuringarticle quality in Wikipedia using the collaborationnetwork [C]//Proceedings of the 2015 IEEE/ACMInternational Conference on Advances in Social NetworksAnalysis and Mining. Paris, France: ACM, 2015:464-471.
[42]	WU L W, RAO Y, FAN X B, et al. A study on thecredibility of information spreaded on social networks[J]. Journal of Chinese Information Processing, 2018,32(2): 1-11 (in Chinese).
[43]	PETERS K, MARUSTER L, JORNA R J. Knowledgeclaim evaluation: A fundamental issue for knowledgemanagement [J]. Journal of Knowledge Management,2010, 14(2): 243-257.
[44]	QIU Q L, DAI F, DONG J F, et al. Research onexplicit-knowledge evaluation system of the enterprises’knowledge pool [J]. Mechanical Engineer, 2012(7): 1-3 (in Chinese).
[45]	LI X S, ZHANG L L, ZHU Z X. Intelligent evaluationmethods for knowledge acquired through data mining[J]. Science Research Management, 2010, 31(Sup 1):32-38 (in Chinese).
[46]	HARDALOVM, KOYCHEV I, NAKOV P. In searchof credible news [C]//International Conference on ArtificialIntelligence: Methodology, Systems, and Applications.Cham, Switzerland: Springer, 2016: 172-180.
[47]	SU J. Credibility measurement of network informationbased on domain knowledge graph [D]. Zhenjiang,China: Jiangsu University of Science and Technology,2018 (in Chinese).
[48]	CUI W. Research and realization of expert systemfor intelligent manufacturing based on uncertainty andfuzzy reasoning [D]. Tianjin, China: Tianjin University,2014 (in Chinese).
[49]	ERTEL W. Introduction to artificial intelligence [M].2nd ed. Cham, Switzerland: Springer, 2017.
[50]	YANG R X, MAO Y L. Discussion on naming recognitionmethod of Chinese scientific research Institutionscatering to knowledge evaluation [J]. Journal of Intelligence,2015, 34(7): 179-183 (in Chinese).
[51]	ZHANG W Q, XIANG Y D, LIU X H, et al. Domainontology development of knowledge base in cardiovascularpersonalized health management [J]. Journal ofManagement Analytics, 2019, 6(4): 420-455