Translated Titles

Using a Knowledge-Integration Model to Construct a Recommendation System for Matching Outpatient Symptoms and Hospital Clinical Departments




戚玉樑(Yu-Liang Chi);陳滄堯(Tsang-Yao Chen);洪智力(Chih-Li Hung)

Key Words

知識分類 ; 知識本體 ; 推論 ; 體徵症狀 ; 疾病 ; Knowledge Categorization ; Ontology ; Inference ; Signs and Symptoms ; Illness



Volume or Term/Year and Month of Publication

39卷1期(2013 / 04 / 01)

Page #

64 - 83

Content Language


Chinese Abstract

知識分類是人類對領域的共同認知,利用結構化方式建立系統性表達,以提供描述、解釋、溝通、及推論。由於實務上的應用問題通常涉及多種領域,因此如何建立它們的知識邏輯是解題關鍵。本研究以個人對體徵症狀(signs & symptoms)的感知為例,探討藉由知識分類及整合,最終能「查詢」特定醫療院所的就診參考。本研究利用知識本體(ontology)技術,發展所需的知識分類與解題模型,主要的內容包括:(1)釐清此議題的知識源內涵,例如徵狀、疾病等知識分類;(2)將一般化的知識源建置為「領域本體」,其內容是由共通性的概念架構及實例共組而成,以利提供其他領域在溝通時做為參考標準或術語;(3)以解題需要來發展各知識源之間的關聯與邏輯,建立目標導向的「任務本體」,再依據各概念的知識框架(schema),收集現況事實為實例知識;(4)最後,發展可推論解題的「語意規則」,並以前述的事實知識為基礎,推導隱含性知識。由實驗結果顯示:本研究發展的知識模型整合程序,強調領域本體、任務本體、及推論規則的模型設計,已初步達到解決以體徵症狀查詢就診科別,也簡化後續知識之維護及擴充,達到知識整合之效用。

English Abstract

Knowledge categorization is the shared recognition of people to a certain knowledge domain. It serves the purposes such as description, interpretation, communication, and inference of a domain of knowledge. Because the application of knowledge in practice for problem-solving can involve multiple domains, therefore how to construct logic relationships among the knowledge categorizations is often the key to problem-solving. This study takes the case of outpatients' perception of signs and symptoms as an example domain to explore how knowledge categorization and integration could help outpatients query and choose from the departments of a healthcare institute at registration. This study uses ontology modeling to develop the needed knowledge categorization and problem-solving models. The major contents include: (1) Clarifying the content of the knowledge sources, including the knowledge categories of symptoms and illness; (2) Constructing a domain ontology of general knowledge sources consisting of common conceptual structure and instances to provide reference standards or terminology when communicating with other domains; (3) Establishing an objective-oriented task-ontology by developing the relationships and logic among the knowledge sources in accordance with the needs of problem-solving, and then collecting existing facts as instance knowledge in accordance with the knowledge schema of the concepts; and (4) Developing a set of inferable semantic rules for problem-solving to infer the implicit knowledge based on the aforementioned factual knowledge. The experiment results show that the procedures of knowledge categorization and integration developed in this study, with the modeling of domain ontology, task ontology, and inference rules, have preliminarily achieved the purpose of solving the problem of matching outpatients' signs and symptoms with the suitable hospital department. Furthermore, the results of this study have simplified the future maintenance and expansion of the domain content knowledge and thus enabled effective knowledge integration.

Topic Category 人文學 > 圖書資訊學
  1. Alavi, M., & Leidner, D.E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107-136.
  2. Chandrasekaran, B., Josephson, J.R., & Benjamins, V.R. (1999). What are ontologies, and why do we need them? IEEE Intelligent Systems, 14(1), 20-26.
  3. Chi, Y.-L. (2009). A consumer-centric design approach to develop comprehensive knowledge-based systems for keyword discovery. Expert Systems with Applications, 36(2), 2481-2493.
  4. Chi, Y.-L., & Chen, H.-C. (2009). Ontology and semantic rules in document dispatching. The Electronic Library, 27(4), 694-707.
  5. Chi, Y.-L., Hsu, T.-Y., & Yang, W.-P. (2006). Ontological techniques for reuse and sharing knowledge in digital museums. The Electronic Library, 24(2), 147-159.
  6. Davenport, T.H., & Prusak, L. (2000). Working knowledge: How organizations manage what they know. Cambridge, MA: Harvard Business Press.
  7. Grüninger, M., & Fox, M.S. (1995, August). Methodology for the design and evaluation of ontologies. Paper presented at the Workshop on Basic Ontological Issues in Knowledge Sharing, International Joint Conference on Artificial Intelligence, Montreal, Quebec, Canada.
  8. Guarino, N. (1995). Formal ontology, conceptual analysis and knowledge representation. International Journal of Human Computer Studies, 43(5), 625-640.
  9. Guarino, N. (1997). Understanding, building and using ontologies. International Journal of Human-Computer Studies, 46(2/3), 293-310.
  10. Horrocks, I., Patel-Schneider, P.F., & Van Harmelen, F. (2003). From SHIQ and RDF to OWL: The making of a web ontology language. Web Semantics: Science, Services and Agents on the World Wide Web, 1(1), 7-26.
  11. Jiang, G., Ogasawara, K., Endoh, A., & Sakurai, T. (2003). Context-based ontology building support in clinical domains using formal concept analysis. Journal of Medical Informatics, 71(1), 71-81.
  12. López de Vergara, J.E.L., Villagrá, V.A., & Berrocal, J. (2004). Applying the web ontology language to management information definitions. IEEE Communications Magazine, 42(7), 68-74.
  13. Richards, D., & Simoff, S.J. (2001). Design ontology in context-a situated cognition approach to conceptual modelling. Artificial Intelligence in Engineering, 15(2), 121-136.
  14. Uschold, M., & Gruninger, M. (1996). Ontologies: Principles, methods and applications. The Knowledge Engineering Review, 11(2), 93-136.
  15. Walczak, S. (1998). Knowledge acquisition and knowledge representation with class: The object-oriented paradigm. Expert Systems with Applications, 15(3/4), 235-244.
  16. 周濟群、戚玉樑、曾建勛(2012)。以詞彙表為 基礎的知識本體雛型建構研究─以「公司治 理」領域知識為例。圖書資訊學研究,6(2), 37-81。 【Chou, Chi-Chun, Chi, Yu-Liang, & Tzeng, Jian-Shiun (2012). A research on how to construct the prototype of knowledge ontology based on glossary - Using the domain knowledge of “corporate governance” as an illustration. Journal of Library and Information Science Research, 6(2), 37-81.】
  17. 戚玉樑、蔡明宏(2007)。以文件為對象的概念萃取 程序建立知識本體的雛型架構。資訊管理學報, 14(3),47-66。 【Chi, Yu-Liang, & Tsai, Ming-Hung (2007). Knowledge acquisition approaches for building ontological conceptual prototypes in document. Journal of Information Management, 14(3), 47-66.】
  18. 陳樂惠、林鼎舜(2011)。運用 OWL 與 JessTab 建 構醫院門診推薦專家系統之研究。醫療資訊雜誌, 20(3),4-22。 【Chen, Le-Hui, & Lin, Ting-Shun (2011). The study of hospital clinic recommended expert system based on OWL and JessTab. The Journal of Taiwan Association for Medical Informatics, 20(3), 4-22.】
  19. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American, 284(5), 34-43.
  20. Feigenbaum, E.A. (1977). The art of artificial intelligence: Themes and case studies of knowledge engineering. Proceedings of Fifth International Joint Conference on Artificial Intelligence (pp. 1014-1029). Cambridge, MA.
  21. Ganter, B., & Wille, R. (1997). Formal concept analysis: Mathematical foundations. Secaucus, NJ: Springer -Verlag New York.
  22. Laudon, K.C., & Laudon, J.P. (2012). Management information systems: Managing the digital firm (Global.). Edingburgh, England: Pearson Education.
  23. Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, November-December, 162-171.
  24. Noy, N.F., & McGuinness, D.L. (2001). Ontology development 101: A guide to creating your first ontology (Technical Report No. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880). Stanford, CA: Stanford Knowledge Systems Laboratory and Stanford Medical Informatics Center.
  25. Noy, N.F., Sintek, M., Decker, S., Crubézy, M., Fergerson, R.W., & Musen, M.A. (2001). Creating semantic web contents with protege-2000. IEEE Intelligent Systems, 16(2), 60-71.
  26. O’connor, M., Knublauch, H., Tu, S., Grosof, B., Dean, M., Grosso, W., & Musen, M. (2005). Supporting rule system interoperability on the semantic web with SWRL. In Y. Gil, E. Motta, V.R. Benjamins, & M.A. Musen (Eds.), The Semantic Web - ISWC 2005 (pp. 974-986). Galway, Ireland: Springer.
  27. World Health Organization. (2004). ICD-10: International statistical classification of diseases and health related problems. Geneva, Switzerland: World Health Organization.
  28. Zack, M.H. (1998). What knowledge-problems can information technology help to solve. In E. Hoadley & I. Benbasat (Eds.), Proceedings of the Americas Conference of AIS (pp. 644-646). Baltimore, MD: Association for Information Systems.
  29. Zirn, C., Nastase, V., & Strube, M. (2008). Distinguishing between instances and classes in the wikipedia taxonomy. In Proceedings of 5th European Semantic Web Conference on the Semantic Web: Research and Applications (ESWC’08) (pp. 376-387). Springer -Verlag: Berlin, Heidelberg.
  30. Kahan, S., & Smith, E. G.(2007)。表解疾病的徵象 與症狀(張晉銓譯)。台北市:合記圖書出版社。 (原著出版年:2004) 【Kahan S., & Smith, E. G. (2007). In a page signs & symptoms (Jin-Quan Zhang Trans.). Taipei: Hochi. (Original work published 2004)】
  31. 安藤幸夫、西尾剛毅(2006)。胃腸肝膽胰臟學習大 百科。新北市:瑞昇。【Yukio, Ando, & Takeki, Nishio (2006). Weichang gandan yizang xuexidabaike. New Taipei: Rising.】
  32. 行政院衛生署中央健康保險局(2013)。國際疾病分 類第十版ICD-10-CM/PCS。檢自:http://www.nhi. gov.tw/webdata/webdata.aspx? menu=23&menu_id =957&webdata_id=3986&WD_ID=957 【National Health Insurance Administration Ministry of Health and Welfare (2013). International statistical classification of disease and related health problems, tenth revision, clinical modification, ICD-10-CM/PCS. Retrieved from http://www.nhi.gov.tw/webdata/webdata. aspx?menu=23&menu_id=957&webdata_id=3986& WD_ID=957】
  33. 阮明淑、溫達茂(2002)。Ontology 應用於知識組織 之初探。佛教圖書館館訊,32,6-17。 【Yuan, Ming-Shu, & Wen, Dar-Maw (2002). Ontology yingyong yu zhishizuzhi zhi chutan. Information Management for Buddhist Libraries, 32, 6-17.】
  34. 孫漢屏(1991)。類神經網路為基礎之智慧型醫院網 路掛號系統(未出版之碩士論文)。中國醫藥學院 醫務管理研究所,台中市。 【Sun, Han-Ping (1991). An intelligent appointment system based on the neural networks (Unpublished master’s thesis). Department of Health Service Administration, China Medical University, Taichung, Taiwan.】
  35. 高誌鍵(2010)。應用服務導向架構於網路掛號系統 ─以某兩家醫院為例(未出版之碩士論文)。佛 光大學資訊學系,宜蘭縣。 【Kao, Chih-Chien (2010). Applying service-oriented architecture to online registration systems: Examples of two hospitals (Unpublished master’s thesis). Department of Applied Information, Fo Guang University. Yilan, Taiwan.】
  36. 黑瀨巖(2005)。圖解消化系統的疾病與機制。新北 市:世茂。 【Iwao, Kurose (2005). Tujie xiaohua xitong de jibing yu jizhi. New Taipei: Coolbook.】
  37. 廖玉里(2002)。聯合網路掛號智慧代理系統之開發 (未出版之碩士論文)。國立陽明大學衛生資訊與 決策研究所,臺北市。 【Liao, Yu-Li (2002). The development of universal hospital web registry intelligent agents (Unpublished master’s thesis). Institute of BioMedical Informatics, National Yang-Ming University, Taipei, Taiwan.】
  38. 廖俊凱(2012)。90%的人生病都掛錯科:權威健檢 師教你看對醫生、做對檢查!臺北市:廣廈。 【Liao, Jun-Kai (2012). 90% de ren shengbing dou guacuoke: Quanwei jianjianshi jiao ni kandui yisheng, zuodui jiancha! Taipei: Guangxia.】
  39. 劉文卿、馮國卿(2003)。以Metadata 為核心發展 金融機構Ontology 之研究。圖書館學與資訊科 學,29(2),45-59。 【Liou, Wen-Ching, & Feng, Kuo-Ching (2003). Developing the ontology for financial institutions based on standardized metadata. Journal of Library & Information Science, 29(2), 45-59.】
Times Cited
  1. 陳修銘(2015)。醫院門診掛號科別與醫師推薦系統。中興大學資訊科學與工程學系所學位論文。2015。1-44。 
  2. 洪嘉澤(2014)。以知識本體技術與探勘方法探討台北都會區道路工程與管理系統之研究。中央大學土木工程學系學位論文。2014。1-233。