Mining positive and negative sequential patterns in data streams with a sliding window

A data stream is an ordered sequence of elements which arrives one by one with positive real time intervals [1]. It is often referred to as streaming data. Dierent from data in traditional static datasets, a data stream is continuous, huge, fast changing, rapid, and infinite. Many applications generate large amount of data streams in real time, such as sensor data generated from sensor networks, online transaction flows in retail chains, Web log and click-streams in Web applications, call records in telecommunications, etc. The nature of streaming data makes it essential to use online algorithms which require only one scan over the data for knowledge discovery [2].