Nowadays, financial data analysis is becoming increasingly important in the business market. As companies collect more and more data from daily operations, they expect to extract useful knowledge from existing collected data to help make reasonable decisions for new customer requests, e.g. user credit category, churn analysis, real estate analysis, etc. Financial institutes have applied different data mining techniques to enhance their business performance. However, simple approach of these techniques could raise a performance issue. Besides, there are very few general models for both understanding and forecasting different financial fields. We present in this paper an integrated model for analyzing financial data. We also evaluate this model with different real-world data to show its performance. © 2012 Springer-Verlag.
CITATION STYLE
Cai, F., Lekhac, N. A., & Kechadi, M. T. (2012). An integrated model for financial data mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7694 LNAI, pp. 306–317). https://doi.org/10.1007/978-3-642-35455-7_28
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