Design and Development of Semantic Ontology for Large Scale Manufacturing Industry with Help of Expert Miner
How to Cite?
Soumitra Singh, Partha Sarathi Chakraborty, S. Nallusamy, K. Balakannan, "Design and Development of Semantic Ontology for Large Scale Manufacturing Industry with Help of Expert Miner," International Journal of Engineering Trends and Technology, vol. 69, no. 5, pp. 186-189, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I5P225
Process mining in industry encourages the professional and invention in industry raw data by machine learning and semantic technologies. Key problematic in trade businesses is drifting between professional and difficult to automate. In this situation, ontologies develop as a substantial technique for characterize manufacturing facts in an engine-understandable method. This information can then be applied by computerized problem resolving techniques to configure the regulator package that synchronizes and controls manufacturing schemes. Also, ontology shows a vital role in development of generating and handling the knowledge. This research illustrates the design and development of semantic knowledge in manufacturing industry using protege tool. This resource description framework is plug-in with java and python software. Integration of the manufacturing ontology produce more effective performance in car manufacturing company to find the car buyer patters effectively using data mining techniques.
Semantic Mining, Ontology, Manufacturing Industry, Knowledge Base, Buyer Patterns, Clustering
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