A Comparative Study of Frequent Pattern Recognization Techniques From Stream Data

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Provided by: The International Journal of Innovative Research in Computer and Communication Engineering
Topic: Big Data
Format: PDF
Mining frequent pattern from data stream is a challenging task. Finding frequent pattern from data streams have been of importance in many application such as stock market prediction, sensor data analysis, network traffic analysis, e-business and telecommunication data analysis. Frequent pattern stream tree is used for maintaining frequent pattern over a period of time using modified FP tree algorithm. This approach maintains tilted time window at each node which consumes larger space. Compact pattern stream tree assumes that only current patterns are of importance and uses sliding window protocol for maintaining it.
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