Knowledge-based evolving clustering algorithm for data stream

Zhaoyang Sun,K Z Mao,Wenyin Tang,Leeonn Mak,Kuitong Xian,Ying Liu

Service Systems and Service Management（2014）

引用 7|浏览6

暂无评分

摘要

In this paper, we present a knowledge-based evolving algorithm for data stream clustering. The basic idea of the new algorithm is to divide data stream into frames, and to incorporate knowledge learned in previous frames into clustering of the following ones. Experimental studies have demonstrated that the evolving learning mechanism leads to improved clustering results compared with conventional incremental clustering algorithm Fuzzy ART and batch-based clustering algorithm k-means.

查看译文

关键词

learning (artificial intelligence),pattern clustering,batch-based clustering algorithm,data stream clustering,fuzzy art clustering,k-means clustering,knowledge-based evolving clustering algorithm,learning mechanism,clustering,data stream,knowledge-based,knowledge based systems,learning artificial intelligence,clustering algorithms,dispersion,k means clustering,classification algorithms,indexes

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要