Mining Maximal Frequent Subtrees Based on Fusion Compression and FP-Tree

Provided by: AICIT
Topic: Big Data
Format: PDF
It is commonly accepted that mining frequent subtrees play pivotal roles in areas like web log analysis, XML document analysis, semi-structured data analysis, as well as biometric information analysis, chemical compound structure analysis, etc. An improved algorithm, i.e. MFPTM algorithm, which based on fusion compression and FP-tree principle, was proposed in this paper to determine a better way to mine maximal frequent subtrees. The algorithm firstly retains subtrees which only contain frequent nodes by fusion compression, then according to FP-tree principle mines frequent subtrees.

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