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Rethinking Audience Clustering in Sports Market using Gossip Protocol


Affiliations
1 Department of Computer Science and Engineering, National Institute of Technology, Srinagar, India
2 Department of Computer Science and Engineering, NIT Srinagar, India
 

Analytics and inferences have found their place in all the business domains varying from large-scale businesses with criticality to small scale business with less criticality. Sports are considered to be big business in its aspects like amount of money spent on it but in its other version like number of people associated with it, it is comparatively a small industry. Sports analytics have changed their dimension both in the manner they are thought about and number of participation from scientific society that grew over the years. Contribution from analytics is being looked from by sports management to enhance various industries associated to it. The authors realize that sports industry is a close, strongly connected group that is very similar in its behavior to a social network. The authors propose a graph theoretic model in context of sports analytics that presents preliminary study of using gossip protocol for sharing information among members of sports oriented social network.


Keywords

Clustering, Gossip Protocol, Sports, Social Network.
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  • Rethinking Audience Clustering in Sports Market using Gossip Protocol

Abstract Views: 297  |  PDF Views: 1

Authors

Asif Ali Banka
Department of Computer Science and Engineering, National Institute of Technology, Srinagar, India
Roohie Naaz
Department of Computer Science and Engineering, NIT Srinagar, India

Abstract


Analytics and inferences have found their place in all the business domains varying from large-scale businesses with criticality to small scale business with less criticality. Sports are considered to be big business in its aspects like amount of money spent on it but in its other version like number of people associated with it, it is comparatively a small industry. Sports analytics have changed their dimension both in the manner they are thought about and number of participation from scientific society that grew over the years. Contribution from analytics is being looked from by sports management to enhance various industries associated to it. The authors realize that sports industry is a close, strongly connected group that is very similar in its behavior to a social network. The authors propose a graph theoretic model in context of sports analytics that presents preliminary study of using gossip protocol for sharing information among members of sports oriented social network.


Keywords


Clustering, Gossip Protocol, Sports, Social Network.

References