Intelligent Data Analysis: Challenges and Solutions
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Intelligent data analysis (IDA) is a method for discovering useful and intriguing information from data to aid in decision making. An IDA task comprises prediction, knowledge discovery, process or system modeling, and constructing knowledge based systems. There are numerous applications of IDA methods in various fields, including finance, marketing, agriculture, and medicine. The demand and availability of more advanced IDA methods has grown in response to the rapidly increasing volume of real-time data that is generated due to an increase in the usage of electronic commerce, web, and multimed...
Intelligent data analysis (IDA) is a method for discovering useful and intriguing information from data to aid in decision making. An IDA task comprises prediction, knowledge discovery, process or system modeling, and constructing knowledge based systems. There are numerous applications of IDA methods in various fields, including finance, marketing, agriculture, and medicine. The demand and availability of more advanced IDA methods has grown in response to the rapidly increasing volume of real-time data that is generated due to an increase in the usage of electronic commerce, web, and multimedia technologies. There are a number of challenges in the application of IDA methods in real-world, such as lack of tools suitable for large data, and lack of user friendly and effective post processing tools. The other challenges include lack of a truly integrated data analysis environment and lack of efficient and automatic preprocessing tools. This book elucidates the challenges and solutions with respect to intelligent data analysis. The topics covered herein offer the readers new insights on this subject.
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