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권영식 교수 ㆍ02-2260-3503 ㆍyskwon@dongguk.edu ㆍ |
학력/연구활동
ㆍKAIST 공학박사ㆍKAIST 공학석사
ㆍ서울대학교 공학사(산업공학)
ㆍ Carnegie Mellon University, Dept' of Machine Learning 연구교수 역임
ㆍUniversity of Virginia, Dept' of System Engineering 연구교수 역임
ㆍUniversity of California, Irvine, Dept' of Computer Science 연구교수 역임
ㆍStanford University, Graduate School of Business, IT & Entrepreneurship Program 이수
학술 및 대외활동
ㆍGeneral Chair, The 28th Int’ Conference on Industrial, Engineering & Applicationsㆍof Applied Intelligent Systems, IEA/AIE 2015, June, 2015, Seoul, Korea
ㆍ한국 BI 데이터 마이닝 학회 회장(2007-2009)
ㆍ한국IT서비스학회 부회장(2004-2012)
ㆍ대한산업공학회 이사(2006-2008)
ㆍ한국생산관리학회 상임이사(2002-2003)
ㆍ한국 RFID/USN협회 자문교수(2004-2011)
ㆍ한국 보건복지정보개발원 IT전문위원(2013-현재)
ㆍ지식경제부 기술혁신 평가위원(2010-2012)
ㆍ정보통신산업진흥원 평가위원(2010-현재)
ㆍ한국표준협회 서비스대상 심사위원(2008년-현재)
ㆍ한국능률협회 한국경영대상 심사위원(2010-현재)
ㆍ한국능률협회 국가품질상 심사위원(2010-현재)
ㆍ한국능률협회 대한민국 마케팅대상 심사위원(2002-2009)
ㆍ소프트웨어공제조합 자문교수(2006-2008)
ㆍ 전문건설공제조합 자문위원(2008-2010)
ㆍ건강보험관리공단 자문위원(2008-2009)
ㆍ서울시 중구청 자문위원 (2003-2010)
ㆍ삼성SDS 자문교수 (2001-2002)
연구분야
ㆍMachine LearningㆍData Mining
ㆍBusiness Analytics
대표논문
-Analyzing Customer Behaviour from Shopping Path Data Using Operation Edit Distance, Applied Intelligence, the Int’Journal of Artificial Intelligence, Neural Networks and Complex Problem-Solving Technologies, Vol.48, No.8, Aug. 2018, Springer
-Emotion Recognition from Text using Deep Neural Networks, The Kore Industrial Engineering Society, Spring Conference, April 1, 2018
-Emotion Recognition with Pairwise Risks, Seoul, The Korea Data Mining Society, Spring Conference, Seoul, April 4, 2018
-Customer Purchasing Behavior Analysis as Alternatives for Supporting in-Store Green Marketing Decision Making, Journal of Substantiality, Vol.9, No.11, Nov.2017
-Development of Long Short Term Memory for detecting Human Emotion in dialogue, Korea BI/Data Mining Society, Fall Conference, November, 2017
-Development of Deep Learning Models for Multi-class Sentiment Analysis, KIIE, Fall Conference, 2017
-Deep Learning Models for Classifying the Emotion Antecedent and Responses in Chatbot, KITS Fall Conference, Nov. 2017
-A Practical Approach to Shopping Path Clustering, Current Approaches in Applied Artificial Intelligence, Lecture Note in Artificial Intelligence, 9101, June, 2015, Springer.
-A Sequence Pattern Matching approach to Shopping Path Clustering, Proceedings of the Int’Conference on Industrial Engineering and Operations Management, Istanbul, Turkey, July 2012.
-A New Approach to Spatial Pattern Clustering based on Longest Common Subsequence with applications to a grocery, IE Interface, Dec. 2011
-Shoppers' Moving Path Analysis in a Grocery using RFID data, Proceedings of the Int’Conference on Robust Statistics, June 2011, Valladolid, Spain.
-Determinants of External Technology Acquisition, 2011, IAENG Int’ Conference on Industrial Engineering, Hong Kong, March 2011.
-Shopping Path Pattern Analysis in a Grocery, Int’Conference on Challenges in Statistics and Operations Research, March 2011, Kuwait University, Kuwait.
-Development of the Intelligent Grocery Analysis systems(i-GAS) for enhancing the Grocery Service Operation, Proceedings in the Int’Conference on Logistics and Transport, Dec. 2010, Queenstown, New Zealand
-Committee Learning Classifier based on Attribute Value Frequency, KIISE, Vol 37. No 4, August 2010
-A Practical Approach to Bankruptcy Prediction for Small Business: Substituting the Unavailable Financial Data for Credit card Sales Information, Vol.37, No.5, Expert Systems with Applications, May 2010