采用项集格生成树的数据结构，将最大频繁项集挖掘过程转化为对项集格生成树进行深度优先搜索获取所有最大频繁节点的过程。
The itemset lattice tree data structure was adopted to translate maximal frequent itemsets mining into the process of depth-first searching the itemset lattice tree.
为解决上述问题，提出了一种深度优先的挖掘加权最大频繁子图的新算法。
To solve the above two problems, authors propose a new depth-first algorithm to discover weighted maximal frequent subgraphs only.
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