提出一种新的方法来提取复杂的图案
Proposition d'une nouvelle approche d'extraction des motifs fermés fréquents
摘要：
这项工作是作为硕士论文项目的一部分完成的。数据量的增加引起了与收集、储存、分析和利用这些数据以创造附加值有关的各种问题。在这个大师中，我们感兴趣的是在事务库中搜索频繁的闭合模式。处理数据的一种方法是将搜索空间划分为子上下文，然后同时探索子上下文。在这种情况下，我们提出了一种新的方法来提取频繁闭项集。其主要思想是更新频繁的封闭模式，其最小的发电机通过应用的初始提取上下文的分区策略。我们的新方法称为UFCIGs-DAC的设计和实施，在测试基地进行搜索。这种方法的主要创新之处在于通过频繁闭合模式和最小生成器的更新来同时探索研究空间。此外，我们的方法可以适用于任何算法的提取频繁的封闭模式，其最小的发电机。
英文摘要：
This work is done as part of a master's thesis project. The increase in the volume of data has given rise to various issues related to the collection, storage, analysis and exploitation of these data in order to create an added value. In this master, we are interested in the search of frequent closed patterns in the transaction bases. One way to process data is to partition the search space into subcontexts, and then explore the subcontexts simultaneously. In this context, we have proposed a new approach for extracting frequent closed itemsets. The main idea is to update frequent closed patterns with their minimal generators by applying a strategy of partitioning of the initial extraction context. Our new approach called UFCIGs-DAC was designed and implemented to perform a search in the test bases. The main originality of this approach is the simultaneous exploration of the research space by the update of the frequent closed patterns and the minimal generators. Moreover, our approach can be adapted to any algorithm of extraction of the frequent closed patterns with their minimal generators.
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。
