The search results got by current search engines generally include a large number of duplicate Web pages. A search results optimization algorithm based on DBSCAN clustering algorithm was proposed.
针对目前搜索引擎搜索结果中普遍存在大量重复网页的现象，提出了一种基于聚类算法DBSCAN的搜索结果优化算法。
Experimental results show that the new algorithm has better performance than Density Based Spatial Clustering of Applications with Noise (DBSCAN).
实验结果表明，新算法较基于密度的带噪声数据应用的空间聚类方法(DBSCAN)具有更好的聚类性能。
Proposes an improved DBSCAN algorithm which can handle non-spatial properties and greatly accelerate the speed of clustering.
文中提出了一种基于DBSCAN的算法，可以处理非空间属性，同时又可以加快聚类的速度。
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