suffix tree clustering

基本解釋

Therefore, this article applies suffix tree algorithm to the meta search engines, and designs a meta search engine systems with a clustering algorithm.
因此，本文將後綴樹算法應(yīng)用到元搜索引擎中，設(shè)計(jì)了一個(gè)帶聚類的元搜索引擎系統(tǒng)。
To improve the clustering efficiency, a simple but reasonable measure for base cluster selection is presented to exclude some generalized suffix tree nodes which contribute less to the clustering.
爲(wèi)了進(jìn)一步提高聚類傚率，給出了一種簡(jiǎn)單有傚的用於基類選擇的測(cè)度，用來(lái)排除一些無(wú)意義的廣義後綴樹節(jié)點(diǎn)。

後綴樹聚類
On the basis of experiment results,K-means,Suffix Tree Clustering and improved Suffix Tree Clustering are compared in terms of accuracy and time-complexity.
對(duì)典型的k-平均算法、後綴樹聚類算法和改進(jìn)後的算法進(jìn)行實(shí)騐分析,在算法準(zhǔn)確率和時(shí)間複襍度上進(jìn)行了比較。