多概念格集成与知识获取方法研究

项目名称： 多概念格集成与知识获取方法研究

项目编号： No.61202018

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 计算机科学学科

项目作者： 王俊红

作者单位： 山西大学

项目金额： 23万元

中文摘要： 概念格是数据分析的一种有效方法，已被成功应用到知识发现等领域，然而面对日益复杂的数据分析需求，传统的单一概念格具有其局限性，研究多概念格集成具有重要的理论意义和应用价值。本项目拟针对单一信息系统、多源信息系统、分布式信息系统，研究多概念格集成的分析描述框架、建模方法以及知识获取，具体内容包括：（1）构建并置和叠置形式背景上的连接算子，建立多概念格集成的分析描述框架；（2）给出多概念格约简的判定定理，设计多概念格的概念选择和格选择方法；（3）给出基于多概念格集成的规则提取算法和规则冗余检测方法，提出基于多Iceberg概念格的频繁项集和关联规则挖掘算法，给出多优势概念格分级规则获取算法。本课题的研究将建立多概念格集成及知识获取的理论和方法体系，为运用智能计算解决实际问题提供新的理论基础与技术支撑。

中文关键词： 多概念格；粒计算；粗糙集；知识获取；概念漂移

英文摘要： Concept lattice theory is an effective method for data analysis, which has been successfully applied in knowledge discovery and other fields. However, traditional single concept lattice shows its limitation for the aquirements of more and more complex data analysis. To address this issue, we aim to develop esembling theory of concept lattices, which has important theoretical significance and applicabale value. The project is to study the analysis description framework, modeling method and knowledge acquisition of multi-concept lattice ensemble in the context of single/multiple source information systems and distributive information systems. Research content mainly includes: (1) building the connection operators in each of juxtaposed and superimposed formal contexts, and forming a description framework of data analysis of multi-concept lattice ensemble; (2) giving the judgment theorem of multi-concept lattice reduction, and designing the methods of concept selection and lattice selection in multiple concept lattices; (3) based on multi-concept lattice, researching rule acquisition method and rule redundancy detection method, proposing frequent itemsets and association rules mining algorithm, and designing efficient grade rule acqusition algorithm. This research will lay the foundation for establishing a system o

英文关键词： Multi-concept lattice；Granular computation；Rough set；Knowledge discovery；Concept drifting