[A late-type star spectra outlier data mining system].

In M star population, some special objects, which may be of magnetic activity, may be giant stars, or may be of other rare properties, are very important for the follow-up observation and the scientific research on galactic structure and evolution. For local bias of M-type star spectral characteristic lines contained in subspace, a late-type star spectra outlier data mining system is given in the present paper. Firstly, for the sample of M stellar spectral characteristic lines indices, its distribution characteristics in attribute spaces are measured by using the sparse factor and sparsity coefficient, and then this sample is discretized and dimension-reduced to the spectral subspace.

[Automatic classification method of star spectrum data based on classification pattern tree].

Frequent pattern, frequently appearing in the data set, plays an important role in data mining. For the stellar spectrum classification tasks, a classification rule mining method based on classification pattern tree is presented on the basis of frequent pattern. The procedures can be shown as follows.

[A post-processing method of classification rule on stellar spectra].

Automatic classification and analysis of observational data is of great significance along with the gradual implementation of LAMOST Survey, which will obtain a large number of spectra data. In classification rules extracted, there is often a great deal of redundancy which will reduce the classification efficiency and quality seriously. In the present paper, a post-processing method of star spectra classification rule based on predicate logic is presented by using predication to describe the classification rules and logical reasoning to eliminate redundant rules.

[Research on two-stage fuzzy clustering method for spectrum data based on PSO].

A novel high-dimensional clustering algorithm is proposed. On the basis of this, a two-stage fuzzy clustering approach, named TSPFCM, is presented. On the first stage, data is clustered by a new clustering method.

[Research on the interrelation analysis system of celestial spectrum data based on constraint FP tree].

It is an effective method of the mankind seeking after the celestial law that the inherent and unknown interrelationships between characteristics of celestial spectrum data and its physical and chemical properties are mined from the mass celestial body spectrum data. In the present paper, the interrelation analysis system of celestial body spectrum data based on constraint FP tree is designed and implemented by using the association rule based constraint FP tree as the way of analyzing celestial spectrum data, and adopting VC++ and Oracle9i as the development tools. At the same time, its software architecture and function modules are outlined.