An Efficient and Fast Algorithm for Mining Frequent Patterns on Multiple Biosequences
Mining frequent patterns on biosequences is one of the important re-search fields in biological data mining. Traditional frequent pattern mining algorithms may generate large amount of short candidate patterns in the process of mining which cost more computational time and reduce the efficiency. In order to overcome such shortcoming of the traditional algorithms, we present an algorithm named MSPM for fast mining frequent patterns on biosequences. Based on the concept of primary patterns, the algorithm focuses on longer pat-terns for mining in order to avoid producing lots of short patterns. Meanwhile by using prefix tree of primary frequent patterns, the algorithm can extend the primary patterns and avoid plenty of irrelevant patterns. Experimental results show that MSPM can achieve mining results efficiently and improves the performance.
Biological sequence Frequent Pattern Mining Primary Patterns
Wei Liu Ling Chen
School of Information Technology, Nanjing Xiaozhuang University, Nanjing, China Institute of Informa School of Information Technology, Nanjing Xiaozhuang University, Nanjing, China National Key Lab of
国际会议
南昌
英文
178-194
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）