NgramPOS a bigram-based linguistic and statistical feature process model for unstructured text classification

NgramPOS a bigram-based linguistic and statistical feature process model for unstructured text classification

Research in financial domain has shown that sentiment aspects of stock news have a profound impact on volume trades, volatility, stock prices and firm earnings. In-depth analysis of stock news is now sourced from financial reviews by various social networking and marketing sites to help improve deci...

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Bibliographic Details
Main Authors: Yazdani, Sepideh Foroozan, Tan, Zhiyuan, Kakavand, Mohsen, Mustapha, Aida
Format: Article
Language:English
Published: Springer 2018
Subjects:
QA76 Computer software
TA Engineering (General). Civil engineering (General)
TA329-348 Engineering mathematics. Engineering analysis
Online Access:http://eprints.uthm.edu.my/5136/1/AJ%202018%20%28843%29%20NgramPOS%20a%20bigram-based%20linguistic%20and%20statistical%20feature%20process%20model%20for%20unstructured%20text%20classification.pdf

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http://eprints.uthm.edu.my/5136/1/AJ%202018%20%28843%29%20NgramPOS%20a%20bigram-based%20linguistic%20and%20statistical%20feature%20process%20model%20for%20unstructured%20text%20classification.pdf

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