首页> 外文会议>IFIP TC12/WG12.3 International Conference on Intelligent Information Processing(IIP2004); 20041021-23; Beijing(CN) >POST SEQUENTIAL PATTERNS MINING: A New Method for Discovering Structural Patterns
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POST SEQUENTIAL PATTERNS MINING: A New Method for Discovering Structural Patterns

机译:序贯后模式挖掘:一种发现结构模式的新方法

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In this paper we present a novel data mining technique, known as Post Sequential Patterns Mining, which can be used to discover Structural Patterns. A Structural Pattern is a new pattern, which is composed of sequential patterns, branch patterns or iterative patterns. Sequential patterns mining plays an essential role in many areas and substantial research has been conducted on their analysis and applications. In our previous work, we used a simple but efficient Sequential Patterns Graph (SPG) to model the sequential patterns. The task to discover hidden Structural Pattern is based on our previous work and sequential patterns mining, conveniently named Post Sequential Patterns Mining. In this paper, in addition to stating this new mining problem, we define patterns such as branch pattern, iterative pattern, structural pattern, and concentrate on finding concurrent branch pattern. Concurrent branch pattern is thus one of the main forms of structural pattern and will play an important role in event-based data modelling.
机译:在本文中,我们提出了一种称为后顺序模式挖掘的新颖数据挖掘技术,该技术可用于发现结构模式。结构模式是一种新模式,它由顺序模式,分支模式或迭代模式组成。顺序模式挖掘在许多领域起着至关重要的作用,并且已经对其分析和应用进行了大量研究。在我们以前的工作中,我们使用了一个简单但有效的顺序模式图(SPG)对顺序模式进行建模。发现隐藏的结构模式的任务是基于我们以前的工作和顺序模式挖掘(通常称为后顺序模式挖掘)。在本文中,除了陈述这个新的挖掘问题之外,我们还定义了诸如分支模式,迭代模式,结构模式之类的模式,并专注于查找并发分支模式。因此,并发分支模式是结构模式的主要形式之一,并将在基于事件的数据建模中发挥重要作用。

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