基于关联规则挖掘的硬CSPs模式研究

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摘要翻译：
有限域约束满足问题是约束规划领域的一个重要研究方向。然而，这一问题尚未引起关联规则挖掘界研究者的重视。关联规则挖掘作为一种流行的数据挖掘技术，有着极其广泛的应用领域，已经成功地应用于多个交叉学科。本文研究了关联规则挖掘技术，提出了一种级联的方法来提取硬CSPS中有趣的模式。据我们所知，这是第一次用数据挖掘技术来研究这一问题。具体来说，我们通过求解所有的CSP实例，生成随机CSP并收集其特征，然后在数据集上应用数据挖掘技术，进一步发现随机生成的CSP的硬度的有趣模式
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英文标题：
《Towards the Patterns of Hard CSPs with Association Rule Mining》
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作者：
Chendong Li
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最新提交年份：
2009
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Databases        数据库
分类描述：Covers database management, datamining, and data processing. Roughly includes material in ACM Subject Classes E.2, E.5, H.0, H.2, and J.1.
涵盖数据库管理、数据挖掘和数据处理。大致包括ACM学科类E.2、E.5、H.0、H.2和J.1中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  The hardness of finite domain Constraint Satisfaction Problems (CSPs) is a very important research area in Constraint Programming (CP) community. However, this problem has not yet attracted much attention from the researchers in the association rule mining community. As a popular data mining technique, association rule mining has an extremely wide application area and it has already been successfully applied to many interdisciplines. In this paper, we study the association rule mining techniques and propose a cascaded approach to extract the interesting patterns of the hard CSPs. As far as we know, this problem is investigated with the data mining techniques for the first time. Specifically, we generate the random CSPs and collect their characteristics by solving all the CSP instances, and then apply the data mining techniques on the data set and further to discover the interesting patterns of the hardness of the randomly generated CSPs
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PDF链接：
https://arxiv.org/pdf/0906.5040

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关键词：关联规则挖掘 关联规则 CSP Presentation satisfaction 作为 规则 研究 data 数据