A STUDY OF ASSOCIATION RULE MINING IN FRAGMENTED ITEM-SETS FOR PREDICTION OF TRANSACTIONS OUTCOME IN STOCK TRADING SYSTEMS
Rajesh Vyankatesh Argiddi, S. S. Apte · 2012
In this research we majorly focus on predicting the behavior of Indian IT stock market. As the stock market is considered to be highly fluctuating, so predicting the behavior of such stock market needs some strong mathematical methods. We propose a technique named Fragment based mining; this method basically deals in grouping the stocks of different shares and producing some kind of association among the shares of different IT companies which helps in predicting the IT stock market. We group the shares based on small and large scale companies from Indian IT stock market data e.g. Bombay Stock Exchange (BSE). And also we will try to show the correctness of our method by applying the method on the historical data and generating some promising rules in the stock data.