Proposed investment decision support system for stock exchange using text mining method
This work aims to design a proposed decision support system (DSS) for helping investors in making investment decision by using rule text mining based algorithm to analyze news headline and implement analyzing pro gram based on a manual analyzed headlines. The news analysis program (NAP) was used as an important stage in making investment decision on sample of the Gulf Cooperation Council (GCC) stock markets using Alarabia.net and Reuters.com which treated as a source of media noise that has an influence on the value of stock quoted stock market. The second kind of data that proposed to use in this system is the financial data of GCC stock market. The resulted data can be used in further steps to make better understanding of stock market companies behavior such as the statistical, data mining calculation for choosing the best period of time that give the best reaction of stock market ratios to the news indicators and using the vector measure construction method (VMCM) for classifying companies according to their response to the news.
2016 Al Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC MITCSA)