원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.9 No.7
2015.07
pp.151-158
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In recent years, most of text classification researches have used a term-based feature approach, but it has problems that those are language dependent and require a large number of data-set for analysis and learning the classification model. This study proposes a SNS message type classification system combining language independent and dependent features that can be used in short message for type classification in social network service environments and verifies the effectiveness of this system.
목차
Abstract
1. Introduction
2. SNS Message Type Classification System
2.1. System Description
2.2. Language Independent Features
2.3. Language Dependent Feature (bag-of-word)
3. Experiments
3.1. Data
3.2. Method
3.3. Results
4. Conclusions and Future Work
References
1. Introduction
2. SNS Message Type Classification System
2.1. System Description
2.2. Language Independent Features
2.3. Language Dependent Feature (bag-of-word)
3. Experiments
3.1. Data
3.2. Method
3.3. Results
4. Conclusions and Future Work
References
저자정보
참고문헌
자료제공 : 네이버학술정보