Title :
Models and methods for prediction problem of evolving graphs
Author :
Chapanond, Anurat ; Krishnamoorthy, Mukkai S.
Author_Institution :
Comput. Sci. Dept. Rensselaer Polytech. Inst. Troy, New York, NY
Abstract :
This paper concentrates on the prediction problem of evolving graphs. We provide five new models and methods for prediction problem of evolving graphs. We experiment each method on real-world evolving graph data which are football competition data, file sharing data, Enron e-mail data, and Eurovision data. Experimental results show that our prediction methods can predict the result with higher accuracy than the random prediction.
Keywords :
graph theory; prediction theory; Enron e-mail data; Eurovision data; file sharing data; football competition data; prediction problem; real-world evolving graph; Artificial intelligence; Computer science; Government; Information analysis; Internet; Partial response channels; Peer to peer computing; Predictive models; Statistical analysis; Uniform resource locators;
Conference_Titel :
Intelligence and Security Informatics, 2008. ISI 2008. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2414-6
Electronic_ISBN :
978-1-4244-2415-3
DOI :
10.1109/ISI.2008.4565052
