期刊名称：International Journal of Electronics Communication and Computer Technology
印刷版ISSN：2249-7838
出版年度：2012
卷号：2
期号：5
页码：231-233
出版社：International Journal of Electronics Communication and Computer Technology
摘要：There has been a lot of research on the application of data mining and knowledge discovery technologies into financial market prediction area. However, most of the existing research focused on mining structured or numeric data such as financial reports, historical quotes, etc. Another kind of data source – unstructured data such as financial news articles, comments on financial markets by experts, etc., which is usually of a much higher availability, seems to be neglected due to their inconvenience to be represented as numeric feature vectors for further applying data mining algorithms. A new hybrid system has been developed for this purpose. It retrieves financial news articles from the internet periodically and using classification mining techniques to categorize those articles into different categories according to their expected effects on the market behaviors, then the results will be compared with the real market data. This classification with 10 cross fold validation combination of algorithms can be applied to do financial market prediction in the future
关键词：Time Series Analysis; Classification; Absolute ;Error; Temporal Data
