Companies widely use survey to identify customer requirements, but the survey has some problems. First of all, the response is passive due to pre-designed questionnaire by companies which are the surveyor. Second, the surveyor needs to have good preliminary knowledge to improve the quality of the survey. On the other hand, text mining is an excellent way to compensate for the limitations of surveys. Recently, the importance of online review is steadily grown, and the enormous amount of text data has increased as Internet usage higher. Also, a technique to extract high-quality information from text data called Text Mining is improving. However, previous studies tend to focus on improving the accuracy of individual analytics techniques. This study proposes the methodology by combining several text mining techniques and has mainly three contributions. Firstly, able to extract information from text data without a preliminary design of the surveyor. Secondly, no need for prior knowledge to extract information. Lastly, this method provides quantitative sentiment score that can be used in decision-making.

1. 서 론
2. 이론적 배경 및 관련 연구
    2.1 요구사항 분석 관련 연구
    2.2 텍스트 마이닝 관련 연구
3. 텍스트 마이닝을 활용한 사용자 핵심요구사항 분석 방법론
    3.1 방법론의 개요
    3.2 방법론의 분석 도구
    3.3 단계별 세부내용
    3.4 방법론 적용의 유의사항
4. 사례적용
    4.1 단계 1 : 객관적 정보분석
    4.2 단계 2 : 주관적 정보분석
    4.3 단계 3 : 키워드 특성분류
    4.4 단계 4 : 핵심 요구사항 파악
5. 결 론
References

• Yoon Sig Shin(한양대학교 일반대학원 경영컨설팅학과) | 신윤식
• Dong Hyun Baek(한양대학교 경상대학 경영학부) | 백동현 Corresponding Author