Optimized Sentiments analysis Approach, Based On Aspects, Attention and Subjectivity notions For Textual Business Intelligence

This article presents the results obtained in applying an innovative and optimized approach to textual semantic analysis in the service of decision-making. Significant improvements have been made in the existing procedures of sentiment and recommendation analysis, and in opinions mining, to enable better-motivated decisions and benefit from big data. These improvements concerned, especially, the support of the notions of aspects, attention and subjectivity to lighten the treatments, well adapted in the context of big data. The results obtained show the interesting contribution of the approach to the specific field of business intelligence (BI) relative to user behaviors analysis.

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