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Design and Development of Abstractness in Graph Mining Technique using Structural Datum
BibTeX
@MISC{Victor_designand,
author = {S. P. Victor and M. Antony and Sundar Singh},
title = {Design and Development of Abstractness in Graph Mining Technique using Structural Datum},
year = {}
}
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Abstract
Abstract-Graphs are everywhere, ranging from social networks and mobile call networks to biological net-works and the World Wide Web. Mining big graphs leads too many interesting applications including cyber security, fraud detection, Web search, recommendation, and many more. In this paper we describe a technique for the conversion of real-time environment to a Graph Mining pattern. We analyze very large, real world graphs with billions of nodes and edges. Our findings include digraph structures in the connected component size distribution. In the future we will extend our research to propose a GraphTemplateConverter for any real-time complex entities.
Keyphrases
graph mining technique structural datum many interesting application web search digraph structure world wide web mining big graph real world graph social network real-time environment mobile call network graph mining pattern biological net-works fraud detection cyber security connected component size distribution real-time complex entity
