인공지능서비스의 특성분석과 품질평가속성에 대한 연구
A Study on Major Characteristic Analysis and Quality Evaluation Attributes of Artificial Intelligence Service
0
조회
0
다운로드
10
인용
0
참고문헌
키워드
초록
Purpose: The purpose of this study is to define various concepts, features, and scopes by examining various previous studies on AI services that are completely different from existing services. It also examines the limitations of existing service quality evaluation methods and studies the characteristics by combining them with various cases of new AI services. And this is to derive and propose quality evaluation attributes of AI service. Methods: The concept and characteristics of artificial intelligence were derived through research and analysis of various previous studies related to artificial intelligence. The key characteristics and quality evaluation items were derived through the KJ method and matching based on the keywords and characteristics derived from previous studies and various cases. Results: Based on the review of various previous studies on the quality of artificial intelligence services, this study presents the main characteristics and quality evaluation items of new artificial intelligence services, which are completely different from existing service quality evaluations. Conclusion: The quality measurement model of AI service is very useful when planning and developing AI-based new products or services because it can accurately evaluate the requirements of consumers using the services of the new AI era. In addition, consumers can be recommended a customized service according to the situation or taste, and can be provided with a customized service based on this.
Abstract
Purpose: The purpose of this study is to define various concepts, features, and scopes by examining various previous studies on AI services that are completely different from existing services. It also examines the limitations of existing service quality evaluation methods and studies the characteristics by combining them with various cases of new AI services. And this is to derive and propose quality evaluation attributes of AI service. Methods: The concept and characteristics of artificial intelligence were derived through research and analysis of various previous studies related to artificial intelligence. The key characteristics and quality evaluation items were derived through the KJ method and matching based on the keywords and characteristics derived from previous studies and various cases. Results: Based on the review of various previous studies on the quality of artificial intelligence services, this study presents the main characteristics and quality evaluation items of new artificial intelligence services, which are completely different from existing service quality evaluations. Conclusion: The quality measurement model of AI service is very useful when planning and developing AI-based new products or services because it can accurately evaluate the requirements of consumers using the services of the new AI era. In addition, consumers can be recommended a customized service according to the situation or taste, and can be provided with a customized service based on this.
참고문헌 (17)
- Charniak, "Introduction to AI" (1985), Addison-Wesley
- Electronic & Information Research Information Center, "Survey results related to artificial intelligence technology", Journal of Electrical Engineering, 43(6), pp.62~65 (2017)
- Voice Assistant Trend and Recognition Survey Results of Artificial Intelligence, "Institute for Information & communication Technology Promotion", 5~30 (2017)
- Jung, Dong Gyu, "Artificial intelligence technology and main applied industry trend", Journal of the Korea Information Science Society, 15(2), pp.21~28 (2017)
- Artificial Intelligence and the Fourth Industrial Revolution, Forum Report, "KCERN", 1~182 (2016)
- 김혜경, "인공지능 쇼핑 정보 서비스에 관한 탐색적 연구", 유통과학연구, 15(4), pp.69~80 (2017), 한국유통과학회[DOI]
- Problems and Improvements of Artificial Intelligence Appliances, Survey report, "Korea Consumer Agency", 1~33 (2017)
- McCord, M. C, "Deep Parsing in Watson IBM", Journal of Research and Development, 56(3) (2012)
- Parasuraman A., "SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality", Journal of Retailing, 64(Spring), pp.12~40 (1988)
- Parasuraman, "E-S-QUAL: A Multi-item Scale for Accessing Electronic Service Quality", Journal of Service Research, 7(3), pp.213~233 (2002)
- 박애스더, "귀국학생의 대학생활에 관한 사례 연구: 부모와 동행하여 중국 생활을 한 경우를 중심으로", 한국청소년연구, 29(3), pp.5~40 (2018), 한국청소년정책연구원[DOI]
- The present and future of artificial intelligence, "Park, Yu Mee", Institute for Industrial Economics and Technology, 64~72 (2018)
- Rich, E., "Artificial intelligence" (1991), McGraw-Hill
- Russell, S., "Artificial Intelligence: A Modern Approach" (2015), Pearson
- Artificial intelligence technology and industrial potential, "Sug, Wang Hun", Electronics and Telecommunications Research Institute, ~ (2015)
- TIPA, "Small Business Roadmap", pp.3~85 (2017)
- Zhang, B. T., "Cognitive Computing : Multisensory Perceptual Intelligence", Communications of the Korean Institute of Information Scientists and Engineers, 30(1), pp.75~87 (2012)