Earticle

초록

영어

The analysis of dissemination information and sources of information in social network services creates an urgent need with the explosive growth of the number of users and serious situation for false information and privacy leakage detection. Observe that the characteristics of randomness and uncontrollability makes malicious users manufacture and spread false malicious information, it is very difficult to find sources of information. A new information dissemination model based on probabilistic hyper-graph (IDMPH) is proposed. The method focuses on randomness for information dissemination process, introduces probabilistic hyper-graph to calculate the value of probability, find the most likely path and the leadership qualities for source nodes. Experimental results show that the conclusions are consistent with actual complex networks, have better ability to identify the path and leader nodes, can be used as basis for analysis of information control and information sources.

목차

Abstract
 1. Introduction
 2. Model-based Definition
 3. Method and Implementation
  3.1. Calculate the  Most Likely Path 
  3.2. Normalization
  3.3. Calculate the Average Value and Variance for Overall Probability
  3.4. Analyze Leader Nodes
 4. Experiments and Analysis
  4.1. Set Parameters for Source Nodes in IDMPH
  4.2. Test and Analysis of Information Dissemination Process
  4.3. Comparative of Process and Characteristics for Information Dissemination
  4.4. Analyze Leader Nodes
 5. Conclusion
 Acknowledgment
 References

키워드

저자

• Min Du [ Institute of Information and Engineering, Hunan University of Science and Engineering, 425100, Peoples Republic of China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605