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Projective Adaptive Resonance Theory Revisited with Applications to Clustering Influence Spread in Online Social Networks

Authors:
Jianhong Wu

Keywords: -projective clustering; nonlinear dynamics in processing high dimensional data; influence soread in online social network.

Abstract:
We revisit the theory and applications of the Projective Adaptive Resonance Theory (PART) neural network architecture for clustering high dimensional data in low dimensional subspaces and nonlinear manifolds. We put a number of PhD theses, research publications and projects of the York University’s Laboratory for Industrial and Applied Mathematics (LIAM) in a coherent framework about information processing delay, high dimension data clustering, and nonlinear neural dynamics. The objective is to develop both mathematical foundation and effective techniques/tools for pattern recognition in high dimensional data.

Pages: 138 to 139

Copyright: Copyright (c) IARIA, 2015

Publication date: July 19, 2015

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-423-7

Location: Nice, France

Dates: from July 19, 2015 to July 24, 2015