suffix tree

基本解釋

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.
為此，我們引入過(guò)程藍(lán)圖改進(jìn)該方法，降低程序的空間復(fù)雜度，并避免將源代碼變換為后綴樹(shù)這一復(fù)雜過(guò)程。
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the updating speed, it makes use of non-compact suffix tree to incrementally insert the new user request and delete the outdated browsing information.
該模型僅保留處于滑動(dòng)窗口之內(nèi)的最近訪問(wèn)序列，從而反映用戶興趣的變化，同時(shí)利用非壓縮后綴樹(shù)增量式添加新的用戶請(qǐng)求和刪除過(guò)時(shí)的瀏覽信息，以提高更新速度。
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;
本算法建立帶后綴鏈的后綴樹(shù)，利用后綴鏈可以快速定位下一后綴內(nèi)結(jié)點(diǎn)的優(yōu)勢(shì)在線性時(shí)間內(nèi)完成后綴樹(shù)的建立；

suffix -tree 后綴樹(shù)
Index suffix tree 索引后綴樹(shù)
Suffix Tree Clustering 算法;后綴樹(shù)聚類(lèi);使用改進(jìn)的基于后綴樹(shù);該系統(tǒng)使用后綴樹(shù)聚類(lèi)
implicit suffix tree 隱式后綴樹(shù)
multi suffix tree 多尾綴樹(shù)

后綴樹(shù)
Then, from session data a concept sequence suffix tree is constructed as a query suggestion model.
接著,該方法從查詢會(huì)話數(shù)據(jù)中建立一棵查詢概念序列后綴樹(shù)。這就是離線的查詢建議模型。
信息搜索
尾綴樹(shù)

后綴樹(shù)
This thesis mainly focuses on the study of suffix tree index technical dealing with bio-sequences and multiple sequences alignment problem in bioinformatics.
本文主要對(duì)適用于生物序列數(shù)據(jù)上的后綴樹(shù)索引技術(shù)和生物信息學(xué)中的多序列比對(duì)算法進(jìn)行了分析和研究。