A Fast Biological Data Mining Algorithm based on Embedded Frequent Subtree

摘要：

In this paper, we present a fast biological data mining algorithm named IRTM based on embedded frequent subtree. We also advance a string encoding method for representing the trees, a scope-list for extending all substrings and some pruning rules which can further reduce the computational time and space cost. Experimental results show that IRTM algorithm can achieve significantly performance improvement over previous works.

关键词： Biological data Data ming Embedded Frequent SubTree

作者: Zhong-xue Yang

作者单位: Department of Information Technology, Nanjing Xiaozhuang College Department of Computer Science,Nanjing University of Aeronautics and Astronautics Nanjing , China

会议类型: 国际会议

会议名称: 2010年IEEE多媒体信息网络与安全国际会议

会议地点: 南京

会议语种:英文

页码: 705-709

在线出版日期: 2010-11-01（万方平台首次上网日期，不代表论文的发表时间）