In the era of big data, the value of Internet public opinion hot spot extraction is particularly prominent. In order to further develop the application value of Internet public opinion hot extraction, this paper constructs the Internet public opinion hot spot extraction framework, and puts forward an Internet public opinion hot spot extraction method VM-Rep based on voting mechanism and MapReduce framework. A heuristic algorithm based on voting mechanism is proposed for the hot spot of Internet public opinion, and MapReduce is used to improve the ability and efficiency of processing massive data. Experimental results show: VM-Rep’s coverage is significantly better than Top-k, K-means and Agglo, and the redundancy of VM-Rep is the least; VM-Rep takes the least time in the four methods, embodies the advantages of VM-Rep method for massive data.
목차
Abstract 1. Introduction 2. Problem Description 3. Internet Public Opinion Hot Spot Extraction Framework 4. Based on Voting Mechanism of Internet Public Opinion Hot Spot Extraction Algorithm 4.1. Based on Voting Mechanism of Internet Public Opinion Hot Spot Extraction Steps 4.2. Based on Voting Mechanism of Internet Public Opinion Hot Spot Extraction Pseudo Code 4.3. Algorithm Accelerate to Strategy 5. Experimental Analysis 5.1. Experimental Environment 5.2. Experimental Results and Analysis Acknowledgements References
키워드
Public opinion hot spotInternet public opinionBig dataVoting mechanismMapReduce platform
저자
Wei Ling [ Management Institute, Harbin University of Science and Technology, China ]
Gao Chang-Yan [ Management Institute, Harbin University of Science and Technology, China ]
보안공학연구지원센터(IJDTA) [Science & Engineering Research Support Center, Republic of Korea(IJDTA)]
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 Database Theory and Application
간기
격월간
pISSN
2005-4270
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Database Theory and Application Vol.9 No.7