標題: A Disk-Based Mining Algorithm for Frequent Pattern Discovery from Big Data in Distributed Computing Environments
作者: Lin, Kawuu W.
Chung, Sheng-Hao
Hsiao, Chun-Yuan
Lin, Chun-Cheng
Chen, Pei-Ling
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: Data mining;Frequent pattern mining;Clustering;Distributed computing
公開日期: 十一月-2016
摘要: In distributed computing environments, frequent pattern mining by a multi-computing node can greatly improve mining efficiency. However, the drawback of memory limitations may cause interruption in the kernel and computing nodes when recursively building a frequent pattern (FP) tree or an FP-growth algorithm. In this paper, we propose disk-based FP-tree generation and node-based clustering mechanisms to solve the insufficient memory problem. Results from empirical evaluations show that the proposed method delivers excellent scalability.
URI: http://dx.doi.org/10.6138/JIT.2016.17.6.20150603c
http://hdl.handle.net/11536/136346
ISSN: 1607-9264
DOI: 10.6138/JIT.2016.17.6.20150603c
期刊: JOURNAL OF INTERNET TECHNOLOGY
Volume: 17
Issue: 6
起始頁: 1259
結束頁: 1268
顯示於類別:會議論文