Analyses of results are also given , comparative experiments show that the beat approach in this paper is better than conventional hierarchy clustering technique , and much better than multivariate statistical analyses such as principle component analyses on dimension reduction based feature encoding 另外比较实验结果表明文中的最好方法其系统性能好于目前广泛采用的分层聚类技术，并远好于多元统计分析技术，例如主成分分析的特徵降维编码。
（ 4 ） at last , the paper focuses on the application of web server cluster technique . based on the analyse of enterprise e - commerce , studied the web server cluster system architecture , and provided a new scheduling policy which supply qos service . it has reference sense for the future application study （ 4 ）对web集群技术实际应用进行了研究，分析了面向企业电子商务应用环境，针对其特点探索研究了面向企业电子商务应用的web集群体系结构；提出了具有qos服务的web集群l7调度算法；该项研究对web集群技术实际应用有一定的指导意义。
( 1 ) puts forward a new text representation model , which originates from the theory of equivalence division of the rough set , defines the similitude of this model , and proposes the approach to calculate the text similitude of this model . ( 2 ) puts the text clustering techniques into the practice of information filtering 提出了一种新的文本表示模型，该模型基于粗糙集的对知识的等价划分的思想，试图保持文本的概念信息：定义了该模型下的粗糙相似度；并提出了基于该模型的计算文本相似度的方法。
Document clustering techniques have been received more and more attentions as a fundamental and enabling tool for efficient organization , navigation , retrieval , and summarization of huge volumes of text documents . the aim of document clustering is to cluster the documents into different semantic classes in an unsupervised manner 文本聚类作为一种对大规模文本信息进行有效地组织、导航、检索和概括汇总的关键的、基本的技术而日益受到关注,其主要目的是在语义空间里以无监督的方式将文本集中的文本划分成不同的类。
This fact implies that the fractal algorithm is very effective and in practical . 2 ) by combining the tabu search and the clustering technique , we propose a hybird algorithm to solve the placement problems , both for the bbl and the gate - array placement . simulation results show that our hybird algorithm is of robustness and effectiveness , it is expected the algorithm is also uesful in other optimization problems . to testify the feasibility of using various computational intelligent algorithm , such as neural networks , genetic algorithm and ant colony system approach in solving a 2 ）首次将禁忌搜索算法与结群技术相结合，并将其分别应用于门阵列布局和bbl布局中，计算机模拟结果表明该算法鲁棒性强、有效，适应性广，适用于大规模门阵列布局和bbl布局问题， 3 ）分别用神经网络技术、遗传算法和蚁群算法对两端线网布线问题进行了研究，并对结果进行了分析比较。
Document clustering techniques have been received more and more attentions as a fundamental and enabling tool for efficient organization , navigation , retrieval , and summarization of huge volumes of text documents . the aim of document clustering technique is to cluster different documents into different semantic classes based on their content in an unsupervised manner 文本聚类作为一种对大规模文本信息进行有效组织、导航、检索和概括汇总的基础、关键技术而日益受到关注,其主要目的是以无监督指导的方式根据文本的内在关系将内容近似的文本分成不同的类。
Through this , the quantity of data transmission will be reduced and working efficiency of system will be enhanced . additionally , we do an effective exploration about the application of cluster technique in jms and a corresponding policy is brought forward . the architecture of arm ( active recovery manager ) is constructed , which promotes the reliability , expansibility and anti - calamity 另外，对集群技术在作业管理系统中的应用作了有效的探索，提出了相应的解决策略，建立了arm ( activerecoverymanager )服务体系，提高了系统的可靠性、可扩充性和抗灾难性。
The main point of this project is to research the theories and applications of artificial neural network ( ann ) which is suitable for large scale science data mining . especially , our research focus include : dimension reduction techniques based on independent component analysis ( ica ) and wavelet - based denoising or compressing techniques for feature extraction in scientific datasets which have complex features ; classify and clustering techniques of ann combination with data grid , back - propagation neural network , self - growing multilevel self - organizing map for large scale knowledge founding in sdm 特别深入研究以独立分量分析( ica )为主的降维技术、以小波神经网络为主的压缩降噪技术解决科学数据特征复杂不便识别的问题;以同网格结合的神经网络、误差反向传播的bp神经网络、自适应多级自组织特征映像网络为主的分类、聚类技术解决科学数据挖掘中的大规模知识发现问题。
This thesis aims to discuss the clustering techniques with the background of large - scale nuclear physics science data mining . first , we introduce the key techniques and the main task in data mining , then we analyze the data preprocessing techniques and clustering techniques combine data mining techniques with science data . from data preprocessing aspect , we propose some methods of segmenting , denoising , integrating and transforming , and we use “ truncation method ” and “ successive difference method ” in data reduction , at last we extract information from the science data 论文基于大规模核物理科学数据挖掘的背景,全面介绍了数据挖掘的关键技术和主要任务,从理论、算法和应用三个层次,结合科学数据的特点来分析预处理技术和聚类方法,提出了很多实用的预处理方法:对hdf5科学数据进行分块、除噪、集成、变换等,同时对它使用“截断法”和“逐层求差法”进行规约,并对数据进行信息提取。
Under this background , we firstly expatiated the classification , primary aspects , and applications in e - commerce of data mining . after we discussed popular clustering techniques in detail , an improved clustering algorithm , adaptive k - means , is presented on the basis of analyzing the advantages and disadvantages of the traditional k - means . the new algorithm is superior to the traditional one that it can determine the cluster number and the initial centroids adaptively , and reduce the blindness and subjectivity to some extent 基于这种应用背景和前提，本文首先系统阐述了数据挖掘的分类、技术以及在电子商务领域的主要应用，重点讨论了其中的聚类技术；在分析现有主要聚类算法的优缺点的基础上，提出了传统k - means算法的一种改进算法? ? adaptivek - means聚类算法，该算法能够自适应地确定聚类的个数以及初始聚类中心，避免了在聚类数目选取上存在的主观性以及初始划分的盲目性，在一定程度上弥补了原算法的不足，并通过实验验证了该算法的有效性。
