A novel approach for data stream clustering using artificial bee colony algorithm
Chong Huan Xu · International Journal of Wireless and Mobile Computing · 2015
This paper presents a novel approach to effectively clustering a large amount of data stream produced by some applications such as large–scale surveillance, network packet inspection and stock market. Owing to the massiveness and forgotten characteristics of the data stream, the proposed approach uses a damped window model to partition them. Then it adopts modified K–means based on the Artificial Bee Colony (ABC) algorithm to cluster this data stream fragment and dynamically update the clustering result. Detailed simulation analysis demonstrates that this algorithm is of high efficiency of space and time and is more stable.