摘要
寻找未知的天文规律是人类探索宇宙奥妙所追求目标之一.利用关联规则来描述天体光谱数据特征与其物理化学性质之间存在的、未知的相关性,是实现该目标的一种有效手段.以国家重大科学工程LAMOST项目为背景,利用一阶谓词逻辑作为天体光谱知识表示技术,提出一种约束FP树及其构造算法,从而有效提高天体光谱数据相关性分析的针对性和效率.并在此基础上,提出一种基于约束FP树的天体光谱数据相关性分析方法.实验结果分析表明,利用该相关性分析方法挖掘天体光谱数据特征和物理化学性质之间存在的相关性,是可行的和有价值的.
To search the unknown laws of celestial bodies is one of the objectives of human exploration of the universe. Utilizing the association rules is an effective way to find out the inherent and unknown interrelationships between characteristics of the celestial spectrum data and its physical and chemical properties. Using the national science project LAMOST as application background, constrained FP tree and its constructing algorithm are presented by taking first order predicate logic as knowledge representation technique of celestial spectrum data. Consequently, the interrelation analysis efficiency and the pertinence of celestial spectrum data are greatly improved. Thus, an interrelation analysis method of celestial spectrum data is proposed. The experimental results validate that the proposed method is feasible and valuable.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2009年第4期639-646,共8页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金(No.60573075)
山西省自然科学基金(No.2006011041)资助项目
关键词
天体光谱数据
相关性分析
关联规则
约束FP树
天体光谱知识
Celestial Spectrum Data, Interrelation Analysis, Association Rule, Constrained Frequent Pattern （FP） Tree, Celestial Spectrum Knowledge
