http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
효과적인 산업재해 분석을 위한 텍스트마이닝 기반의 사고 분류 모형과 온톨로지 개발
안길승,서민지,허선,Ahn, Gilseung,Seo, Minji,Hur, Sun 한국안전학회 2017 한국안전학회지 Vol.32 No.5
Accident analysis is an essential process to make basic data for accident prevention. Most researches depend on survey data and accident statistics to analyze accidents, but these kinds of data are not sufficient for systematic and detailed analysis. We, in this paper, propose an accident classification model that extracts task type, original cause materials, accident type, and the number of deaths from accident reports. The classification model is a support vector machine (SVM) with word occurrence features, and these features are selected based on mutual information. Experiment shows that the proposed model can extract task type, original cause materials, accident type, and the number of deaths with almost 100% accuracy. We also develop an accident ontology to express the information extracted by the classification model. Finally, we illustrate how the proposed classification model and ontology effectively works for the accident analysis. The classification model and ontology are expected to effectively analyze various accidents.
소셜 네트워크 서비스 기반의 4세대 지식관리시스템 설계 방안
안길승(Gilseung Ahn),권민성(Minsung Kwon),강창욱(Changwook Kang),허선(Sun Hur) Korean Institute of Information Scientists and Eng 2016 정보과학회논문지 Vol.43 No.5
Currently, corporations have introduced the knowledge management system that utilizes knowledge effectively for practical purpose and development of core ability. However, existing knowledge systems have failed to share the knowledge content due to lack of elements that encourage the members to participate in the system. In this study, we designed a novel knowledge management system that employs the structure of social network service (SNS). More precisely, screen layout according to function and several algorithms to improve user friendliness and produce integrated knowledge content are recommended. The proposed SNS-based knowledge management system encourages the enterprise members to participate in the system to produce and share valuable knowledge contents.