关键词: XML文档, 高斯核函数, 核聚类算法, 量子遗传算法, XML聚类

Abstract: This paper mainly targets on XML clustering with kernel methods for pattern analysis and the quantum genetic algorithm。Then, a new method based on the quantum genetic algorithm and kernel clustering algorithm was proposed. To eliminate the XML documents first, the vector space kernels kernel matrix was generated with frequenttag sequence, the initial clustering and clustering center with the Gaussian kernel functions were solved, then the quantum genetic algorithms initial populations were constructed by the initial clustering center structure. Clustering of the globally optimal solutions was obtained through the combination of quantum genetic algorithm and kernel clustering algorithm. The experimental results show that the proposed algorithm is superior to the improved kernel clustering algorithm and K-means in good astringency, stability and overall optimal solutions.

Key words: XML document, Guassian kernel function, kernel clustering algorithm, quantum genetic algorithm, XML clustering