Proper resource allocation on research requires accurate forecasting for the future research activities. Forecasting task can be done using judgmental or numerical analysis. Bibliometric analysis is a quantitative method to determine the trend of research area by counting the frequency of certain keywords using journal publication or patents. This paper reports the implementation of our new forecast combination method which selects the best methods used by similar validation dataset on Indonesian journal database, namely the Garuda dataset, especially on the subject of Science and Technology. The experimental result indicates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, the emerging research topics for the next few years can be objectively identified.
목차
Abstract 1. Introduction 2. Theoretical Background 2.1. Forecast Combinations 2.2. Model Selection 2.3. Time Series Similarity 2.3. Growth Rate 3. Experimental Setup 3.1. Methodology 3.2. Datasets 3.3. Performance Evaluation 3.4. Hardware and Tools 4. Result and Discussion 4.1. Comparison among Individual Predictor 4.2. Combination of Models using Similarity Measure 4.3. Emerging Topics 4. Conclusion References
키워드
Science & Technology (S&T)emerging topicsensembleforecastingresearch topicssimilarity measuretime series
저자
Indra Budi [ Faculty of Computer Science University of Indonesia ]
Rizal Fathoni Aji [ Faculty of Computer Science University of Indonesia ]
Agus Widodo [ Faculty of Computer Science University of Indonesia ]
보안공학연구지원센터(IJSEIA) [Science & Engineering Research Support Center, Republic of Korea(IJSEIA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Software Engineering and Its Applications
간기
월간
pISSN
1738-9984
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Software Engineering and Its Applications Vol.7 No.5