Trend mining in social networks: from trend identification to visualization

Author:

Nohuddin Puteri N. E.1,Sunayama Wataru2,Christley Rob3,Coenen Frans4,Setzkorn Christian5

Affiliation:

1. Faculty of Science and Technology of Defense at National Defense University of Malaysia; Kuala Lumpur Malaysia

2. Graduate School of Information Sciences; Hiroshima City University; Hirioshima Japan

3. Department of Epidemiology & Population Health; Institute of Infection and Global Health, University of Liverpool and National Centre for Zoonosis Research; Leahurst Neston UK

4. Department of Computer Science; University of Liverpool; Liverpool UK

5. EA Technology, Capenhurst Technology Park; Capenhurst UK

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Reference36 articles.

1. Self-Organising Maps

2. Agrawal , R. T. Imielinski A. Swami 1993 Mining association rules between sets of items in large databases Proceeding of the ACM SIGMOD International Conference on Knowledge Discovery and Data Mining KDD 93 207 216

3. Agrawal , R. R. Srikant 1994 Fast algorithms for mining association rules Proceedings of the 20th Very Large Data Bases Conference VLDB 94 487 499

4. Agrawal , R. R. Srikant 1995 Mining sequential patterns Proceedings of the 11th International Conference on Data Engineering ICDE 95 3 14

5. Choudhury , M.D. H. Sundaram A. John D.D. Seligmann 2008 Can blog communication dynamics be correlated with stock market activity? Proceedings of the 19th ACM Conference on Hypertext and hypermedia ACM 55 60

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