We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Many database applications require the analysis and processing of data streams. In such systems, huge amounts of data arrive rapidly and their values change over time. The variati...
Lv-an Tang, Bin Cui, Hongyan Li, Gaoshan Miao, Don...
Spam, also known as Unsolicited Commercial Email (UCE), is the bane of email communication. Many data mining researchers have addressed the problem of detecting spam, generally by...
The rapid advance of computer technologies in data processing, collection, and storage has provided unparalleled opportunities to expand capabilities in production, services, comm...
In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...