Time Series Analysis of Temporal Data by Classification using Mean Absolute Error

There has been a lot of research on the application ofdata mining and knowledge discovery technologies into financialmarket prediction area. However, most of the existing researchfocused on mining structured or numeric data such as financialreports, historical quotes, etc. Another kind of data source –unstructured data such as financial news articles, comments onfinancial markets by experts, etc., which is usually of a muchhigher availability, seems to be neglected due to theirinconvenience to be represented as numeric feature vectors forfurther applying data mining algorithms. A new hybrid systemhas been developed for this purpose. It retrieves financial newsarticles from the internet periodically and using classificationmining techniques to categorize those articles into differentcategories according to their expected effects on the marketbehaviors, then the results will be compared with the real marketdata. This classification with 10 cross fold validation combinationof algorithms can be applied to do financial market prediction in the future