Financial market predictions using Web mining approaches

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. With text preprocessing (document representation) technologies, this thesis makes use of this kind of data, specifically financial news articles, to

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