Abstract
Recently, Formal Concept Analysis (FCA) have been widely used for various purposes in many different domains such as data mining, machine learning, knowledge management and so on. In this paper, we introduce FCA as the basis for a practical and well founded methodological approach for data analysis which identifies conceptual structures among data sets. As well as, we propose a FCA-based data analysis for discovering association rules by using polarity from social contents. Additionally, we show the experiments that demonstrate how our data analysis approaches can be applied for knowledge discovery by using association rules.
Publisher
Trans Tech Publications, Ltd.
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