An objective of this work is to contextualize the analysis of large and multi-faceted data sources. Consider for example, health research in the context of social characteristics. Also there may be social research in the context of health characteristics. Related to this can be requirements for contextualizing Big Data analytics. A major challenge in Big Data analytics is the bias due to self selection. In general, and in practical settings, the aim is to determine the most revealing coupling of mainstream data and context. This is technically processed in Correspondence Analysis through use of the main and the supplementary data elements, i.e., individuals or objects, attributes and modalities.
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