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A dynamic genetic algorithm for clustering web pages

机译:网页聚类的动态遗传算法

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摘要

Though the hybrid clustering algorithm (HCA)[10] is very effective to cluster Web pages, it needs the auto k value calculation (AKVC) method[13] to calculate the number of clusters in advance and its clustering result is affected by the number. A dynamic genetic algorithm(DGA) is designed in this paper by improving the AKVC method and the HCA's population, genetic operators and fitness function. The experiments show that DGA can obtain a more accurate number of clusters than AKVC and more accurate clusters of Web pages than HCA.
机译:尽管混合聚类算法(HCA)[ 10 ]对网页进行聚类非常有效,但它需要自动k值计算(AKVC)方法[ 13 ]来计算集群的数量预先决定,其集群结果受数量的影响。通过改进AKVC方法和HCA的种群,遗传算子和适应度函数,设计了一种动态遗传算法(DGA)。实验表明,与AKVC相比,DGA可以获得更准确的簇数,而与HCA相比,DGA可以获得更准确的网页簇。

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