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Data mining or Knowledge Discovery in Databases (KDD) is a new field in information technology that emerged because of progress in creation and maintenance of large databases by combining statistical and artificial intelligence methods with database management. Data mining is used to recognize hidden patterns and provide relevant information for decision making on complex problems where conventional methods are inecient or too slow. Data mining can be used as a powerful tool to predict future trends and behaviors, and this prediction allows making proactive, knowledge-driven decisions in businesses. Since the automated prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools, it can answer the business questions which are traditionally time consuming to resolve. Based on this great advantage, it provides more interest for the government, industry and commerce. In this paper we have used this tool to investigate the Euro currency fluctuation. For this investigation, we have three different algorithms: K, IBK and MLP and we have extracted Euro currency volatility by using the same criteria for all used algorithms. The used dataset has 21,084 records and is collected from daily price fluctuations in the Euro currency in the period of10/2006 to 04/2010.

Keywords

Euro Currency Fluctuation, Data Mining, Stock Market, Knowledge Discovery in Databases.
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