当数据库中的项目数目较大且事务数量巨大时，频繁模式增长算法内存开销很大，可能导致内存空间不足的现象。
When there are a great many of items and transactions in the database, frequent-pattern growth algorithm needs more additional computer memory, which may cause the lack of memory.
采用FP -bonsai pruning而实现更快的频繁模式增长(Frequent Pattern Growtt)算法。
Faster Frequent Pattern Growth (FPGrowth) using FP-bonsai pruning.
随着对大量结构化数据分析需求的增长，从图集合中挖掘频繁子图模式已经成为数据挖掘领域的研究热点。
With the increasing demand of massive structured data analysis, mining frequent subgraph patterns from graph datasets has been an attention-deserving field.
随着对大量结构化数据分析需求的增长，从图集合中挖掘频繁子图模式已经成为数据挖掘领域的研究热点。
With the increasing demand of massive structured data analysis, mining frequent subgraph patterns from graph datasets has been an attention-deserving field.
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