Automated frequency-based statistical and linguistic feature process models for financial news sentiment classification

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Automated frequency-based statistical and linguistic feature process models for financial news sentiment classification

This thesis utilizes sentiment classification task within the field of artificial intelligence for financial news using the combination of machine learning, linguistics, and statistical methods. The motivation for this approach comes from human emotion and vital information that lies in the finan...

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Bibliographic Details
Main Author:	Yazdani, Sepideh Foroozan
Format:	Thesis
Language:	English
Published:	2017
Subjects:	Time-series analysis Finance-Mathematical models-Computer programs Eimeria tenella
Online Access:	http://psasir.upm.edu.my/id/eprint/113985/ http://psasir.upm.edu.my/id/eprint/113985/1/113985.pdf

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