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

• 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; http://eprints.uthm.edu.my/5136/

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...