摘要翻译：
数据挖掘算法现在能够高效地处理海量数据。各种各样的模式可能会被发现，并可能对知识的总体发展产生一些重大影响。在许多领域中，最终用户可能希望通过数据挖掘工具挖掘他们的数据，以便提取可能影响其业务的模式。然而，在这种情况下，这些用户往往会被大量的模式所淹没。此外，一些隐私问题或商业问题可能导致用户无法自己挖掘数据。因此，用户可能不可能执行集成各种约束的许多实验，以便集中在他们想要提取的特定模式上。模式的后处理可能是解决这一缺陷的一个方法。因此，在本文中，我们提出了一个允许最终用户管理模式集合的框架。我们建议使用一种高效的数据结构，在该结构上可以使用一些代数运算符来检索或访问模式库中的模式。
---
英文标题：
《A Model for Managing Collections of Patterns》
---
作者：
Baptiste Jeudy (LAHC), Christine Largeron (LAHC), Fran\c{c}ois
  Jacquenet (LAHC)
---
最新提交年份：
2009
---
分类信息：

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。
--

---
英文摘要：
  Data mining algorithms are now able to efficiently deal with huge amount of data. Various kinds of patterns may be discovered and may have some great impact on the general development of knowledge. In many domains, end users may want to have their data mined by data mining tools in order to extract patterns that could impact their business. Nevertheless, those users are often overwhelmed by the large quantity of patterns extracted in such a situation. Moreover, some privacy issues, or some commercial one may lead the users not to be able to mine the data by themselves. Thus, the users may not have the possibility to perform many experiments integrating various constraints in order to focus on specific patterns they would like to extract. Post processing of patterns may be an answer to that drawback. Thus, in this paper we present a framework that could allow end users to manage collections of patterns. We propose to use an efficient data structure on which some algebraic operators may be used in order to retrieve or access patterns in pattern bases.
---
PDF链接：
https://arxiv.org/pdf/0902.1080