Knowledge Discovery from Static Datasets to Evolving Data Streams and Challenges

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Mining data streams has recently become an important active research work and more widespread in several fields of computer science and engineering. It has proven successfully in many domains such as wireless sensor networks, ATM transactions, search engines, web analysis and weather monitoring. Data steams can be considered a subfield of machine learning, data mining and knowledge discovery. Data mining is a step in the process of knowledge discovery from large amount of data. Traditional data mining techniques cannot be easily applied to the data stream mining due to unique characteristics of data streams.
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