Abstract Implementation of Graph Mining Technique using Structural Datum in Viral Marketing
M. Antony Sundarsingh1, S.P.Victor2
1M. Antony Sundarsingh, Research Scholar, M.S University, Tirunelveli, (Tamil Nadu), India.
2Dr. S.P. Victor, HOD, CS, St.Xaviers College, Tirunelveli (Tamil Nadu), India.
Manuscript received on July 20, 2013. | Revised Manuscript received on August 15, 2013. | Manuscript published on August 30, 2013. | PP: 385-388 | Volume-2, Issue-6, August 2013.  | Retrieval Number: F2110082613/2013©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Graph mining and marketing has become an important topic of research recently because of numerous applications to a wide variety of business problems in computational biology, chemical data analysis, drug discovery and communication networking. Nowadays Graphs play a vital role everywhere, occupying the social networks and mobile networks to biological net-works and the World Wide Web. Mining big graphs leads too many interesting applications including marketing, news groups, community mining, and many more. In this paper we describe a technique for the implementation of real-time marketing to a Graph Mining pattern. Our findings include designs to survey different aspects of graph mining and management, and provide a compendium for other researchers in the field. The results are revealed for selecting the optimized maximum priority based network selection to implement the marketing action. In the future we will extend our research to propose a Graph-Analysis Implementer for any real-time complex entities.
Keywords: Graph mining, Graph pattern, Graph template, Graph network.