...nd multi-task learning）、特征选择（feature selection）、社会网络（social networks）、图数据挖掘（mining of graph data）、时空数据分析（tem
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The surge of social network analysis also makes graph (network) data management become one of the hottest research topic within the database and data mining community.
社会网络分析的兴起也使得图(网络)数据管理成为了当前数据库和数据挖掘领域的一个研究热点。
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。
Frequent patterns mining is an important aspect of data mining and includes mining transaction, sequence, tree and graph.
频繁模式挖掘是数据挖掘领域的一个重要方面，研究内容一般包括事务、序列、树和图。
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