Processing and extracting meaningful knowledge from count data is an important problem in data mining. The volume of data is increasing dramatically as the data is generated by da...
Recently, there has been significant interest in developing space and time efficient solutions for answering continuous summarization queries over data streams. While these techni...
Nagender Bandi, Ahmed Metwally, Divyakant Agrawal,...
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
Abstract— This work presents a sampling data stream algorithm for wireless sensor networks (WSNs). The proposed algorithm is based on sampling techniques applied to data histogra...
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...