Abstract
Most of the existing algorithms for mining frequent patterns could produce lots of projected databases and short patterns which could increase the time and memory cost of mining. In order to overcome such shortcoming, a fast and efficient algorithm named FBPM for mining frequent patterns in biological sequence is proposed. We first present the concept of primary pattern, and then use prefix tree for mining frequent primary patterns. A pattern growth approach is also presented to mine all the frequent patterns without producing large amount of irrelevant patterns. Our experimental results show that FBPM not only improves the performance but also achieves effective mining results.
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