The suffix tree is a very important data structure, which finds a wide variety of applications in many areas related to string processing.
后缀树是一种非常重要的数据结构，它在与字符串处理相关的各种领域里有着非常广泛的应用。
There are three major steps: establish suffix tree, search for common strings and link common strings.
该算法分为三个主要步骤—建立后缀树，寻找公共子串，连接公共子串。
We present a quick method to mine the frequent path and the reachable set and probability of web pages browsed by users based on the suffix tree;
给出了基于后缀树用户浏览频繁路径、页面可达集和可达概率的快速计算方法；
It addresses the method of identifying the accurate tandem repeat in detail after analyzing suffix tree and suffix array algorithms of string matching.
在分析了后缀树和后缀数组字符串匹配算法的基础上，详细阐述了基于后缀数组的精确串联重复序列识别方法。
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，本文将后缀树算法应用到元搜索引擎中，设计了一个带聚类的元搜索引擎系统。
This thesis mainly focuses on the study of suffix tree index technical dealing with bio-sequences and multiple sequences alignment problem in bioinformatics.
本文主要对适用于生物序列数据上的后缀树索引技术和生物信息学中的多序列比对算法进行了分析和研究。
In order to reduce the space complexity of the arithmetic and avoid transforming the source code top-suffix tree, the method is improved based-on process blueprint.
为此，我们引入过程蓝图改进该方法，降低程序的空间复杂度，并避免将源代码变换为后缀树这一复杂过程。
Second, general suffix tree algorithm is used to mine the key path from user's all navigation paths, and using key path to cluster all users into different interest groups.
其次，提出从导航路径中利用构造复合后缀树的方法来挖掘用户关键路径，并利用关键路径将用户聚类成不同的兴趣群。
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.
为了进一步提高聚类效率，给出了一种简单有效的用于基类选择的测度，用来排除一些无意义的广义后缀树节点。
The algorithm is based on suffix-tree with suffix link, make full use of the character of suffix link, rapidly position the next suffix internal node, to accomplish the suffix tree in linear time;
本算法建立带后缀链的后缀树，利用后缀链可以快速定位下一后缀内结点的优势在线性时间内完成后缀树的建立；
The algorithm is based on suffix-tree with suffix link, make full use of the character of suffix link, rapidly position the next suffix internal node, to accomplish the suffix tree in linear time;
本算法建立带后缀链的后缀树，利用后缀链可以快速定位下一后缀内结点的优势在线性时间内完成后缀树的建立；
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