类关联词约束的K-Means半监督文本聚类方法

提出了一种利用类关联词和K-Means聚类算法实现对文本文档进行分类的方法。类关联词是与类主题相关、能反映类主题的单词或短语。根据文档中包含的类关联词,形成初始聚类中心。在聚类算法过程中,类关联词提供的信息被用来约束待分类文档与聚类中心的相似度比较,加快了算法的执行。实验证明了算法的有效性。     

移动自组网协作策略研究与分析

针对移动自组网中自私节点拒绝转发数据包的服务请求,影响整体网络性能的问题进行研究,基于经济学中提出的博弈理论,描述了节点检测记录相邻节点的协作率而识别自私节点的方法,提出了主动能量制约策略AECS和基于统计信息的节点协作重复博弈策略LTFT,分析表明该策略和方法能够有效激励协作并孤立自私节点,能有效的解决网络性能与节点收益的权衡问题,在一定程度上解决节点的协作问题。     

基于点云几何与形状特征的曲面重构算法

提出一种新的利用点云进行曲面重构的算法,该算法基于点云的几何与形状特征,根据点云的几何分布进行分类和按照点的局部形状特征进行分类,对每类点进行局部网格重构,并进行后续处理以修补拓扑和几何错误。实验结果表明,该算法强健有效,能生成高质量的网格,并能较好地保持模型的几何与形状特征。     

基于决策树规则的分类算法研究

在商业利益的驱动下,人们不断地深入研究决策树算法.为了提高分类的精度,提出了一种基于决策树规则的分类算法.通过C4.5决策树算法得出决策规则,计算决策规则的长度,准确率与覆盖率,对所得的决策规则依次按照规则长度与准确率的乘积大小、长度的大小、覆盖率的大小对规则集进行排序构造分类器,选择优选权最高的规则进行匹配分类.实验结果表明,与C4.5算法相比,该方法的分类精度有所提高.     

Segmentation of ultrasound images by using a hybrid neural network

A hybrid neural network is presented for the segmentation of ultrasound images.

Feature vectors are formed by the discrete cosine transform of pixel intensities in region of interest (ROI). The elements and the dimension of the feature vectors are determined by considering only two parameters: The amount of ignored coefficients, and the dimension of the ROI.

First-layer-nodes of the proposed hybrid network represent hyperspheres (HSs) in the feature space. Feature space is partitioned by intersecting these HSs to represent the distribution of classes. The locations and radii of the HSs are found by the genetic algorithms.

Restricted Coulomb energy (RCE) network, modified RCE network, multi-layer perceptron and the proposed hybrid neural network are examined comparatively for the segmentation of ultrasound images.     

Uncertain Classification of Fault-Prone Software Modules

Many development organizations try to minimize faults in software as a means for improving customer satisfaction. Assuring high software quality often entails time-consuming and costly development processes. A software quality model based on software metrics can be used to guide enhancement efforts by predicting which modules are fault-prone. This paper presents statistical techniques to determine which predictions by a classification tree should be considered uncertain. We conducted a case study of a large legacy telecommunications system. One release was the basis for the training dataset, and the subsequent release was the basis for the evaluation dataset. We built a classification tree using the TREEDISC algorithm, which is based on ² tests of contingency tables. The model predicted whether a module was likely to have faults discovered by customers, or not, based on software product, process, and execution metrics. We simulated practical use of the model by classifying the modules in the evaluation dataset. The model achieved useful accuracy, in spite of the very small proportion of fault-prone modules in the system. We assessed whether the classes assigned to the leaves were appropriate by statistical tests, and found sizable subsets of modules with uncertain classification. Discovering which modules have uncertain classifications allows sophisticated enhancement strategies to resolve uncertainties. Moreover, TREEDISC is especially well suited to identifying uncertain classifications.     

Classification of hand postures against complex backgrounds using elastic graph matching

A system for person-independent classification of hand postures against complex backgrounds in video images is presented. The system employs elastic graph matching, which has already been successfully applied for object and face recognition. We use the bunch graph technique to model variance in hand posture appearance between different subjects and variance in backgrounds. Our system does not need a separate segmentation stage but closely integrates finding the object boundaries with posture classification.     

基于Radon变换和SWT的旋转不变纹理分类

提出了一种应用Radon变换和离散平稳小波变换(SWT)的旋转不变纹理分类算法。该方法首先对纹理图像进行Radon变换将旋转转化为平移,再用具有平移不变性的离散平稳小波对变换后的图像滤波并计算各子带的能量值组成旋转不变特征向量,最后利用支持向量机实现纹理图像的分类。将本方法与其它旋转不变纹理分类法进行比较,实验结果表明,提出的方法能有效地提高正确分类率。     

IP分类技术研究综述

作为网络互联的核心设备，路由器必须以吉比特乃至更高的速度对IP包进行处理，网络应用的发展要求路由器除了具备传统的路由转发功能之外，还必须有能力支持防火墙，提供QoS，流量计费等一系列功能，这些都要求路由器根据包头对IP包进行分类，根据分类完成数据包的不同处理，本文全面地介绍了IP分类技术研究的最新成果，总结了解决IP分类问题的一般思想和并详细介绍了IP分类的典型算法，本文对其中三种算法在虚拟环境下做了评测，比较了它们的优缺点，最后指出了进一步的研究方向。     

中文检索系统中查询的扩展

本文基于向量空间模型，提出了根据类别体系的层次结构，将特征项进行层次存储利用特征项所示的概念范畴的不同，以用户原始查询做进一步的扩展，文中详细介绍了用户查询扩展的方法，给出了查找某一特征项的下两层子特征项的算法。