|
 
|
[Fad19] Sentiment analysis approach based on machine learning of latent semantics from textual (unstructured) data
Revue Internationale avec comité de lecture : Journal RIHM, vol. 19(2), pp. 30, 2019Mots clés: Digital Humanities, (Big, Linked, Smart) Data, deep learning, machine learning, Data Mining, Text Mining, opinion mining, sentiments analysis, Natural Language Processing (NLP), semantics
Résumé:
This article presents a research work and the results obtained, through an approach, that aims to develop new innovative methods in the specific aera of textual semantic analysis, in the service of decision-making. Significant improvements have been made in the existing procedures of sentiments analysis and recommendations, and opinions mining, to enable better motivated decisions and benefit from big data. The results obtained show the interesting contribution of the approach to the specific field of digital humanities relative to user behaviors analysis.
BibTeX
| @article { | |||
| Fad19, | |||
| title | = | "{Sentiment analysis approach based on machine learning of latent semantics from textual (unstructured) data}", | |
| author | = | "H. Fadili", | |
| journal | = | "RIHM", | |
| year | = | 2019, | |
| volume | = | 19, | |
| number | = | 2, | |
| pages | = | "30", | |
| } | |||
