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An Improved Artificial Immune System Model for Link Prediction

  • Mengmeng WangEmail author
  • Jianjun Ge
  • De Zhang
  • Feng Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11013)

Abstract

Currently, online social network has derived a series of hot research problems, such as link prediction. Many results in undirected and dynamic network have been achieved. Targeted at on-line microblogs, this paper first build user’s dynamic emotional indices and network topological structure features based on time series of user’s contents and network topological information. Then, we improve artificial immune system and deploy it to predict the existence and direction of link. Experiments on real-world dataset demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of temporal information in link prediction.

Keywords

Link prediction Improved artificial immune system Time series Emotional indices Dynamic social network 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mengmeng Wang
    • 1
    Email author
  • Jianjun Ge
    • 1
  • De Zhang
    • 1
  • Feng Zhang
    • 1
  1. 1.Information Science Academy, China Electronics Technology Group CorporationBeijingChina

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