Open AccessA scientific review of soft-computing techniques and methods for stock market prediction
Author(s) -
Muhammad Rabiul Islam,
Imad Fakhri Taha Alshaikhli,
Ahmed Abdulkadir
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.5.10049
Subject(s) - data science , social media , computer science , web mining , stock market , field (mathematics) , key (lock) , stock (firearms) , soft computing , sentiment analysis , data mining , world wide web , artificial intelligence , web service , engineering , artificial neural network , mechanical engineering , paleontology , mathematics , computer security , horse , pure mathematics , biology
Information could be power if most technological approach engaged in the era of IT. Web based text mining is one of the approach that could be analyzed in many ways through soft-computing methods and techniques. The analytical result has shown that different methods of text mining have several advantages with the gap of knowledge that is required to improve. This paper explores the performance of various methods and its impact on specific text mining field such as web based financial text analysis for stock prediction. Key research area of financial text mining is becoming one of the potential research field based on the source of online news, forums, blogs or social media.