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Game Theory studies strategic situations where agents select different actions to maximize their returns. Game Theory has recently drawn attention from computer scientists because of its use in artificial intelligence and cybernetics. This paper presents a frame work of integrating Data Mining with Game Theory. Due to the reason of huge amount of data, it is hard for Game Theory alone to perform the modeling analysis. Data mining assists Game Theory to deal with the large amount of data and finds hidden rules to improve game analysis.

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Existence of interoperability within the enterprises is essential for textile supply chain to efficiently face the challenges from contemporary competitors, to find new business opportunities and to render better customer service. Exchange of business documents, being semantically consistent, is the way to achieve interoperability. However, heterogeneity of the structures of the enterprises poses challenges for establishing interoperability. Ontology based semantic interoperability framework has now been proven as an effective solution for enterprise interoperability. In this paper, the existing ontology-based interoperability solutions in the context of textile supply chain have been compiled and research gaps have been identified. The ontological methods, such as unified process for ontology (UPON) and methontology have been analyzed, and UPON have been shown as a suitable ontology development method for textile supply chain.