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• W2387751128 abstract "Big data are generated from a variety of sources having different representation forms and formats, it raises a research question as how important data relevant to a business context can be captured and analyzed more accurately to represent deep and relevant business insight. There is a number of existing big data analytic methods available in the literature that consider contextual information such as the context of a query and its users, the context of a query-driven recommendation system, etc. However, these methods still have many challenges and none of them has considered the context of a business in either data collection or analysis process. To address this research gap, we introduce a big data analytic technique which embeds a business context in terms of the significance level of a query into the bedrock of its data collection and analysis process. We implemented our proposed model under the framework of Hadoop considering the context of a grocery shop. The results exhibit that our method substantially increases the amount of data collection and their deep insight with an increase of the significance level value." @default.
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• W2387751128 date "2015-12-01" @default.
• W2387751128 modified "2023-09-23" @default.
• W2387751128 title "Business context in big data analytics" @default.
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• W2387751128 doi "https://doi.org/10.1109/icics.2015.7459846" @default.
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