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arXiv 1005.0239cs.DS
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关于有向无圈图中频繁模式的寻找

On Finding Frequent Patterns in Directed Acyclic Graphs

Andrea Campagna, Rasmus Pagh

摘要:

给定一个有向无环图的标记顶点,我们考虑的问题,找到最常见的标签序列(“迹”)之间的所有路径的图(一些最大长度m)。由于路径的数量可以是巨大的,我们提出了新的算法,其时间复杂度仅取决于图的大小,和最频繁的痕迹的相对频率。此外,我们应用流算法的技术,以实现仅依赖于带宽的空间使用,而不是不同的痕迹的数量。考虑的抽象问题模型的各种任务,发现频繁的事件序列模式。我们的动机来自于哥本哈根机场行李手推车上200万个RFID读数的数据集。发现频繁的乘客移动模式的问题映射到上述问题。我们报告这个数据集的实验结果。

英文摘要:

Given a directed acyclic graph with labeled vertices, we consider the problem of finding the most common label sequences ("traces") among all paths in the graph (of some maximum length m). Since the number of paths can be huge, we propose novel algorithms whose time complexity depends only on the size of the graph, and on the relative frequency epsilon of the most frequent traces. In addition, we apply techniques from streaming algorithms to achieve space usage that depends only on epsilon, and not on the number of distinct traces. The abstract problem considered models a variety of tasks concerning finding frequent patterns in event sequences. Our motivation comes from working with a data set of 2 million RFID readings from baggage trolleys at Copenhagen Airport. The question of finding frequent passenger movement patterns is mapped to the above problem. We report on experimental findings for this data set.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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