DOIONLINE 
DOIONLINE Publish In |
International Journal of Management and Applied Science (IJMAS)-IJMAS |
 Journal Home Volume Issue |
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Issue |
Volume-4,Issue-2 ( Feb, 2018 ) | |||||||||
Paper Title |
Stock Market Prediction using KMP Algorithm for Fast News Search and Effective Data Mining Methods | |||||||||
Author Name |
Faten Alzazah | |||||||||
Affilition |
Computer science and engineering Department, New York Institute of Technology, USA | |||||||||
Pages |
63-68 | |||||||||
Abstract |
Before evolution of text mining techniques, data mining and statistical techniques were used to predict the stock movement based only on past prices, their weakness is that they depend heavily on structured data .Which neglects the important influence of unstructured information .In this paper, we will use the most important data mining techniques using Exponential smoothing and Linear Trend Line concurrently with text mining using fast String matching algorithm( KMP algorithm) for stock market prediction. Keywords- KMP Algorithm, News Articles search, Data Mining, Exponential Smoothing, Linear Trend Line, Stock Market Prediction. | |||||||||
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