一种混合文本分类方法研究

文本自动分类是信息检索领域的一个重要研究方向。一些标准的机器学习算法像支持向量机已经成功地运用到了这一领域。不幸的是高维的输入向量严重的影响了分类速度,而支持向量机核函数参数的确定影响到分类的精度。为了提高分类精度和分类速度,本文提出了一种混合分类算法,首先用粗糙集理论对向量进行约简,然后采用基因算法对支持向量机的核函数参数进行优化。实验证明我们提出的算法是有效的。     

学术评价的多变量指标探讨

结合集成影响指标(I3)和h指数构成I3型多变量指标框架,获得发文矢量X=(X1,X2,X3)和引文矢量Y=(Y1,Y2,Y3)、集成发文指数I3X=X1+X2+X3和集成引文指数I3Y=Y1+Y2+Y3等多变量指标。实证研究显示:整体h核分布适用于评价学者,h核指数X1和Y1适用于评价大学的核心影响力,集成指数I3X和I3Y适合替代期刊影响因子JIF。多变量指标为学术评价提供了结合I3和h指数优势的多维视角,可丰富学术评价测度。图5。表4。参考文献18。附表3。     

卫生政策知识服务平台信息过滤理论与实践

信息过滤是卫生政策知识服务平台建设中的核心技术,在系统研究信息过滤的几种经典方法的基础上,确立将向量空间模型作为该平台的信息过滤方法,并进行一定的改进,以避免传统向量空间模型的不足。在字段间权重设定方面,采用信息检索过程中评价检索效果的两个经典指标,即查全率和查准率进行过滤效果的评价,并进行反复测试,最终确定各类资源不同字段在信息过滤过程中设置的权重及阈值,成功完成信息采集、信息分类、信息主动推送等功能。     

停用词表对基于SVM的中文文本情感分类的影响

运用非结构化信息挖掘,对网络评论情感进行分析是一个非常重要的方法。本文基于Web客户评论情感文本,在情感文本预处理过程中使用四种不同的停用词表,采用两种不同的特征选择方法,选用著名的TF-IDF权重计算方法,使用基于RBF核函数的支持向量机方法的分类器实现了对携程网上采集的4000个酒店客户评论情感文本的分类研究。通过实验,分析了不同特征选择方和停用词表的使用对客户评论文本情感分类的影响,提出了基于情感文本分类的有效的停用词表。     

基于变权综合的大学生数学能力评价方法

为了切实提高大学生的数学能力,结合大学数学教学的特点和影响大学生数学能力的因素,建立了评价大学生数学能力的指标体系,应用变权综合方法,可对不同专业的大学生采用不同的权重,避免固定权重引起的评价结果不合理的现象,并通过实例证明该方法的客观性和科学性。     

Control vector optimization and genetic algorithms for mixed-integer dynamic optimization in the synthesis of rice drying processes

Rice drying synthesis is an essential operation that has to be done carefully and cost-effectively. Rice is harvested at high moisture content and hence must be dried within 24 h for safe storage. However, improper drying can cause fissuring in the rice grain, and thus greatly reduce its market value. Multi-pass drying systems are therefore used to gradually bring moisture content to desired level.The problem of rice synthesis, considered in this study, seeks the configuration of units and their corresponding operating conditions that maximize rice quality. This problem is formulated as a mixed-integer dynamic optimization problem. The integer part of the problem reflects process alternatives while the dynamic part originates from nonlinear differential-algebraic equations describing the drying behavior of a rice grain.Clearly such a formidable problem is not easy to solve. Hence, we propose an approach that makes use of two algorithms: a genetic algorithm to search for the best configuration of units and a control vector parameterization approach that optimizes the operating conditions for each configuration. We demonstrate the effectiveness of the approach on a case study.     

A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as "bag of concepts" that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall.     

建构公共权益矢量的和谐行政理念

在公共权益矢量的价值取向上,从三个层面上重新界说公共行政理念的丰富内蕴。在价值评判的构架内,努力实践扩张公共领域的施政策略;公共行政理念的意蕴被叙述为将部分政府职能(私权)让渡给公共领域,予以扩张公共权力。在科学发展实践的框架内,效益概念被表述为综合效益的诉求和整体效能的优化;和谐行政理念的意蕴被表述为将部分私有权利出让给公共领域,予以扩张公共权益和公共环境。在整体认知的模块内,彰显公共权益矢量的涨盈状态。     

基于SVM和粗糙集理论的董事会效率评价研究

本文构建了影响董事会效率的指标体系,并首次采用支持向量机方法(SVM)建立了董事会效率评价的五级分类模型,通过粗糙集理论的属性约简方法来确定最优的输入指标组合.实验结果表明,本文建立的董事会效率评价模型的判别精度要优于已有模型,而通过对惩罚矩阵的合理调整,模型的判别精度可以进一步提高.     

基于VAR和VEC模型的杭州市三次产业结构分析

通过对过去文献的综述,鉴于传统的经济建模方法分析及存在的不足,结合经济计量分析的特点,提出了基于向量自回归(vector auto regression,VAR)及向量误差修正(vector error correction,VEC)模型的经济数据的分析方法,阐述了该方法在经济计量分析中的优点,并介绍了VAR和VEC的模型构建.通过杭州市1978-2008年三次产业数据的实例分析,揭示了杭州市三次产业之间的关系,其分析结果与杭州实际状况相吻合,具有指导意义,能为国家或地区的政策制定和投资策略指明方向.