A Fast and Efficient Algorithm for Finding Frequent Items over Data Stream

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Provided by: Academy Publisher
Topic: Data Management
Format: PDF
In recent years, researchers have paid more attention to mining stream data. Mining frequent item sets from stream data is an important task in stream data analysis. Frequency is a fundamental characteristic in many data mining tasks such as association rule mining and iceberg queries. It has applications in many areas such as sensor data mining, business decision support, analysis of web query logs, direct marketing, network measurement, and internet traffic analysis. Correspondingly, the input stream data could be stock tickers, bandwidth statistics for billing purposes, network traffic measurements, web-server click streams, and data feeds from sensor networks.
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