Recently, with the increase in demand for big data analysis, related techniques and tools are being developed, which makes it possible to utilize data that was difficult to analyze by traditional methods. Topic modeling is a useful technique for deriving topics from a vast amount of text, and is often used in research on trends and predictions of academic research or science and technology. However, the topic derived from the topic modeling is a combination of words presented on the basis of the frequency and probability of simultaneous occurrence, and cannot describe the importance or priority of each word. Therefore, in this study, we applied AHP (Analytic Hierarchy Process) technique to evaluate the priority of the result derived from topic modeling (Topic). In this study, bibliographic data (total of 15,888 articles) of academic researches related to consulting were collected and used in the analysis of this study in order to suggest prioritization method using Topic-Modeling and AHP.

• 김민관(한양대학교 지식서비스연구소, Institute of Knowledge Service, Hanyang University) | Min Kwan Kim
• 이용(한양대학교 일반대학원 경영컨설팅학과, School of Management Consulting, Hanyang University) | Yong Lee
• 한창희(한양대학교 경상대학 경영학부, Department of Business Administration, Hanyang University) | Chang Hee Han