This thesis mainly focuses on the study of suffix tree index technical dealing with bio-sequences and multiple sequences alignment problem in bioinformatics .

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Implementation of Chinese and English Clustering Engine Based on Improved Suffix Tree Algorithm

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At the same time by adopting the zoning searching method the algorithm constructs a suffix tree for each frequent page node and then mines continuous frequent access paths by visiting the tree .

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Subsequently we analyzed the design selection and computation of the sample kernel for different applications . ( 2 ) For the computing of the string kernel we designed and adopted a data structure called pruning suffix tree .

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The pruning suffix tree combines the suffix tree which has suffix chain and the trie-tree which computing the kernel value in the leaf . But it uses less space than suffix tree and computes faster than the trie-tree .

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An Improved Text Clustering Algorithm of Generalized Suffix Tree

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The paper has discussed a text clustering algorithm based on suffix tree named STC . After analyzing some flaws of this algorithm a more effective approach based on PAT-array and Fuzzy clustering is proposed in order to improve the quality of clustering .

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It addresses the method of identifying the accurate tandem repeat in detail after analyzing suffix tree and suffix array algorithms of string matching .

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Suffix Tree Based Label Generation Method for Web Search Results Clustering

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The vague kernel also improves the speed of matching characters using the pruning suffix tree . Finally we designed and realized a classification model for protein .

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Based on these criterions it takes three document clustering algorithms for assessment with experiments . The comparison and analysis show that STC ( Suffix Tree Clustering ) algorithm is better than k-Means and Ant-based clustering algorithms .

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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 ;

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For example : the path expression template-match method the structural joins based on B + tree method the suffix tree index method recoding path expression into a special index method and utilizing XML schema to optimize path expression method etc.

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Based on the research of these algorithms ` design and the analysis of their performance a pair-wise sequence alignment algorithm based on suffix tree is implemented .

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While the data type of input data is a string type this paper realized a statistical method based on general general suffix tree model for frequent string .

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SHOC Lingo algorithm that combined vector space model ( VSD Model ) and the suffix tree document model not only considering the words of the location information but also consider the statistical properties of words had the good development in the STC foundation .

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Faced to network content security we review other representation method and propose a representation method based on suffix tree model ( STM ) .

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According to different storage methods of child suffix tree we introduce several searching technology .

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Then based on partial suffix tree presents a new parallel algorithm of suffix tree which can construction large suffix tree in memory and more perfect to very large sequences .

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Using a suffix tree as input which is constructed by DNA sequences and a search algorithm which is base on suffix trees as measure this method outputs a classified table of element repeats finally .

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Research of a Suffix Tree Based Automatic Wrapper Generation Method

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There are three major steps : establish suffix tree search for common strings and link common strings .

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In order to improve the updating speed it makes use of non-compact suffix tree to incrementally insert the new user request and delete the outdated browsing information .

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High-frequency words extracting algorithm based on suffix tree is used to extract content features of items and the use of thesaurus can be avoided .

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When the data file is processed beforehand the thesis proposes three types of index basic suffix tree index optimal suffix tree index and cluster index .

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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 .

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The second part includes the index of child suffix tree and some other information for finding the location of every child suffix tree in disk quickly .

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In order to enhance the efficiency of the algorithm the suffix tree was improved . The leaf lists are stored in internal nodes of suffix tree .

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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 .

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A Spam Detection Method on Backbone Network Based on Suffix Tree

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