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SADI: Stochastic Approach to Compute Degree of Importance in Web-Based Information Propagation

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 575)


The problem of information propagation (IP) is being studied theoretically but its practical implementation is quite limited as there are many underlying challenges to be resolved. One core problem found in the analysis of IP in dynamic web-based networks (DWBN) such as in social networks is the lack of light weight mechanism to compute the effective node identity. This paper presents a framework using Stochastic Approach to compute the Degree of Importance (DoI) to explore the most influential nodes residing in the dynamic network. The approach explores the influential nodes in any form of operational states of the nodes using probability theory. The model is evaluated with a massive set of open large data of DWBN to validate its effectiveness with the execution time to compute DoI.


  • Information propagation
  • Social network
  • Influential node
  • Web-based network
  • Dynamic network
  • Graph theory

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The work reported in this paper is supported by the college through the TECHNICAL EDUCATION QUALITY IMPROVEMENT PROGRAMME [TEQIP-II] of the MHRD, Government of India.

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Correspondence to Selva Kumar Shekar .

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Shekar, S.K., Nagappan, K., Rajendran, B. (2017). SADI: Stochastic Approach to Compute Degree of Importance in Web-Based Information Propagation. In: Silhavy, R., Silhavy, P., Prokopova, Z., Senkerik, R., Kominkova Oplatkova, Z. (eds) Software Engineering Trends and Techniques in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 575. Springer, Cham.

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