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1)  frequent subgraphquery
频繁子图查询
2)  frequent query pattern
频繁查询模式
1.
XML-based mining algorithm of complete frequent query pattern;
基于XML的完全频繁查询模式挖掘算法
3)  frequent subgraph
频繁子图
1.
New efficient width-first algorithm for mining frequent subgraph;
宽度优先的频繁子图高效挖掘新算法
2.
In order to solve the problem,this paper propose a new method called FSM(frequent subgraph mining) to find frequent subgraph and prove corresponding theoritics to guarantee the exactness of FSM.
该文通过引入子图同构和结构同构的概念,借助贪婪搜索算法和完全级别搜索算法的思想,结合图论和频繁项目集的挖掘算法,提出了一种新的频繁子图挖掘算法——FSM(frequent subgraph mining)。
3.
An alternate way to solve these problems is to represent the transactions of those domains by graph,and find the frequent subgraphs by using graph-based data mining techniques.
一种解决的方法就是用图的形式表示这些领域的事务,然后利用基于图论的数据挖掘技术发现频繁子图。
4)  frequent subgraphs
频繁子图
1.
Due to the frequent subgraphs mining generate a great results set, this restricts the algorithm performance to some extent, and mining maximal frequent subgraphs can effectively reduce the results set of the frequent subgraphs.
由于频繁子图挖掘会产生巨大的结果集,在一定程度上制约了算法性能,而最大频繁子图挖掘可以有效缩减频繁子图的结果集。
2.
Therefore it is imperative to improve the efficiency of mining the frequent subgraphs.
随着图的广泛应用,图的规模不断扩大,因此提高频繁子图挖掘效率势在必行。
5)  subgraph query
子图查询
1.
Many challenges arise in subgraph query processing of graph-structured XML data.
研究了图结构XML数据上子图查询处理,给出了一系列高效的处理算法。
6)  frequenct Hamilton subgraph
频繁Hamilton子图
补充资料:频繁
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