基于相似度计算的本体映射优化方法

在基于相似度计算的本体映射中，相似度计算量大的主要原因是待映射概念和待计算属性过多。该文采用过滤策略，利用候选映射策略和信息增益策略减少待映射概念和待计算属性数量。该过滤策略充分利用本体特点和数据挖掘思想，有效滤除没有计算意义的概念和属性，减少了相似度计算量。实验结果证明，滤除的概念和属性对映射效果的影响很小。

Optimizing Method for Ontology Mapping Based on Similarity Computation

Outlier mining, aim of which is to discover the abnormal data objects in the data set, is an important research aspect in the data mining. The traditional outlier mining algorithms are based on the characteristics of item set, and unsuitable for the application in the multi-objective decision and synthetical evaluation. This paper presents an outlier mining algorithm based on the grey relation analysis. This algorithm is able to mine outliers by the number of the synthetical evaluation and avoid choosing the user-specified threshold. Experimental results show that this algorithm can detect all outliers efficiently in data set, and the mined outliers are coincident and objective.