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A New Approach of Feature Selection for Text Categorization

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Wuhan University Journal of Natural Sciences 2006年第5期11卷 1335-1339页

作者： CUI Zifeng xu Baowen ZHANG Weifeng xu junling School of Computer Science and Engineering Southeast University Nanjing 210096 Jiangsu China Department of Computer Science and Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003 Jiangsu China

This paper proposes a new approach of feature selection based on the independent measure between features for text categorization. A fundamental hypothesis that occurrence of the terms in documents is independent of each other, widely used in the probabilistic models for text categorization （TC）, is discussed. However, the basic hypothesis is incom plete for independence of feature set. From the view of feature selection, a new independent measure between features is designed, by which a feature selection algorithm is given to ob rain a feature subset. The selected subset is high in relevance with category and strong in independence between features, satisfies the basic hypothesis at maximum degree. Compared with other traditional feature selection method in TC （which is only taken into the relevance account）, the performance of feature subset selected by our method is prior to others with experiments on the benchmark dataset of 20 Newsgroups.

关键词： feature selection independency CHI square test text categorization

ISTC: A New Method for Clustering Search Results

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Wuhan University Journal of Natural Sciences 2008年第4期13卷 501-504页

作者： ZHANG Wei xu Baowen ZHANG Weifeng xu junling School of Computer Science and Engineering Southeast University Nanjing 211189 Jiangsu China State Key Laboratory of Software Engineering WuhanUniversity Wuhan 430072 Hubei China Department of Computer Nanjing University of Posts andTelecommunications Nanjing 210003 Jiangsu China

A new common phrase scoring method is proposed according to term frequency-inverse document frequency （TFIDF） and independence of the phrase. Combining the two properties can help identify more reasonable common phrases, which improve the accuracy of clustering. Also, the equation to measure the in-dependence of a phrase is proposed in this paper. The new algorithm which improves suffix tree clustering algorithm （STC） is named as improved suffix tree clustering （ISTC）. To validate the proposed algorithm, a prototype system is implemented and used to cluster several groups of web search results obtained from Google search engine. Experimental results show that the improved algorithm offers higher accuracy than traditional suffix tree clustering.

关键词： Web search results clustering suffix tree term frequency-inverse document frequency (TFIDF) independence of phrases

Stable Initialization Scheme for K-Means Clustering

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Wuhan University Journal of Natural Sciences 2009年第1期14卷 24-28页

作者： xu junling xu Baowen ZHANG Weifeng ZHANG Wei HOU Jun School of Computer Science and Engineering Southeast University Nanjing 211189 Jiangsu China State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 Hubei China Department of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 Jiangsu China

Though K-means is very popular for general clustering, its performance, which generally converges to numerous local minima, depends highly on initial cluster centers. In this paper a novel initialization scheme to select initial cluster centers for K-means clustering is proposed. This algorithm is based on reverse nearest neighbor （RNN） search which retrieves all points in a given data set whose nearest neighbor is a given query point. The initial cluster centers computed using this methodology are found to be very close to the desired cluster centers for iterative clustering algorithms. This procedure is applicable to clustering algorithms for continuous data. The application of the proposed algorithm to K-means clustering algorithm is demonstrated. An experiment is carried out on several popular datasets and the results show the advantages of the proposed method.

关键词： clustering unsupervised learning K-means initialization

A New Feature Selection Method for Text Clustering

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Wuhan University Journal of Natural Sciences 2007年第5期12卷 912-916页

作者： xu junling xu Baowen ZHANG Weifeng CUI Zifeng ZHANG Wei School of Computer Science and Engineering Southeast University Nanjing 210096 Jiangsu China State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 Hubei China Department of Computer Science and Engineering Nanjing University of Posts and Telecommunications Nanjing 210003 Jiangsu China

Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this paper, a new feature selection method for text clustering based on expectation maximization and cluster validity is proposed. It uses supervised feature selection method on the intermediate clustering result which is generated during iterative clustering to do feature selection for text clustering; meanwhile, the Davies-Bouldin＇s index is used to evaluate the intermediate feature subsets indirectly. Then feature subsets are selected according to the curve of the Davies-Bouldin＇s index. Experiment is carried out on several popular datasets and the results show the advantages of the proposed method.

关键词： feature selection text clustering unsupervised learning data preprocessing

Progress in niobium-based oxides as anode for fast-charging Li-ion batteries

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Energy Reviews 2023年第2期2卷 62-79页

作者： Fuqiang Xie junling xu Qizhong Liao Qingqing Zhang Binyun Liu Lianyi Shao Junjie Cai Xiaoyan Shi Zhipeng Sun Ching-Ping Wong School of Materials and Energy Guangdong University of TechnologyGuangzhou510006China Guangzhou Nano New Material Technology Co. Ltd.Guangzhou510006China Guanghua Institute of Sci-Tech(Guangdong)Co. Ltd.Guangzhou510006China School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGAUnited States

With the increasing popularity of electric/hybrid vehicles and the rapid development of 3C electronics,there is a growing interest in high-rate energy storage *** rapid development and widespread adoption of lithiumion batteries(LIBs)can be attributed to their numerous advantages,including high energy density,high operating voltage,environmental friendliness,and lack of memory ***,the progress of LIBs is currently hindered by the limitations of energy storage materials,which serve as vital ***,there is an urgent need to address the development of a new generation of high-rate energy storage materials in order to overcome these limitations and further advance LIB ***-based oxides have emerged as promising candidates for the fabrication of fast-charging Li-ion batteries due to their excellent rate capability and long *** review paper provides a comprehensive analysis of the fundamentals,methodologies,and electrochemistries of niobium-based oxides,with a specific focus on the evolution and creation of crystal phases of Nb_(2)O_(5),fundamental electrochemical behavior,and modification methods including morphology modulation,composite technology,and carbon ***,the review explores Nb_(2)O_(5)-derived compounds and related advanced characterization ***,the challenges and issues in the development of niobiumbased oxides for high-rate energy storage batteries are discussed,along with future research perspectives.

关键词： Energy storage materials Fast-charging Li-ion batteries Niobium-based oxides Modification Nb_(2)O_(5)-Derived compounds Advanced characterization techniques

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局灶性皮层发育不良影像学研究进展

中国实用神经疾病杂志 2025年第1期28卷 104-108页

作者：任东楠徐俊玲郑州大学人民医院(河南省人民医院) 河南郑州450003

局灶性皮层发育不良(FCD)是药物难治性癫痫的常见病因之一。手术切除致痫灶是目前治疗FCD所致药物难治性癫痫最有效的方式。影像学检查是诊断FCD的常见手段,术前发现病灶并精确定位对手术方案的制定及患者术后的效果至关重要。近年来随... 详细信息

局灶性皮层发育不良(FCD)是药物难治性癫痫的常见病因之一。手术切除致痫灶是目前治疗FCD所致药物难治性癫痫最有效的方式。影像学检查是诊断FCD的常见手段,术前发现病灶并精确定位对手术方案的制定及患者术后的效果至关重要。近年来随着科学技术的发展,影像学检查相关的硬件和软件设施及后处理技术也越来越先进,能更早期、更精确地发现致痫灶,对指导最佳手术方案的制定,追求术后无癫痫发作及更少的神经心理学损伤具有重要意义。因此,本文就近几年提高FCD检出率的相关影像学研究进行综述,以期为临床医生在抉择术前评估方法时提供更详尽的参考。

关键词：局灶性皮层发育不良难治性癫痫磁共振成像正电子发射计算机断层显像术前定位

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基于互信息的无监督特征选择

计算机研究与发展 2012年第2期49卷 372-382页

作者：徐峻岭周毓明陈林徐宝文东南大学计算机科学与工程学院南京210096 计算机软件新技术国家重点实验室(南京大学) 南京210093 南京大学计算机科学与技术系南京210093

在数据分析中,特征选择可以用来降低特征的冗余,提高分析结果的可理解性和发现高维数据中隐藏的结构.提出了一种基于互信息的无监督的特征选择方法(UFS-MI),在UFS-MI中,使用了一种综合考虑了相关度和冗余度的特征选择标准UmRMR(无监督... 详细信息

在数据分析中,特征选择可以用来降低特征的冗余,提高分析结果的可理解性和发现高维数据中隐藏的结构.提出了一种基于互信息的无监督的特征选择方法(UFS-MI),在UFS-MI中,使用了一种综合考虑了相关度和冗余度的特征选择标准UmRMR(无监督最小冗余最大相关)来评价特征的重要性.相关度和冗余度分别使用互信息来度量特征与潜在类别变量之间的依赖和特征与特征之间的依赖.UFS-MI同时适用于数值型和非数值型特征.在理论上证明了UFS-MI的有效性,实验结果也表明UFS-MI可以达到与传统的特征选择方法相当甚至更好的性能.

关键词：特征选择无监督特征选择互信息最小冗余-最大相关无监督最小冗余-最大相关

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公共服务提供:基于电子政府的分析框架

科研管理 2010年第5期31卷 22-26页

作者：徐军玲北京大学经济学院博士后流动站北京100871 华中师范大学管理学院湖北武汉430079

电子政府的应用能够使政府在虚拟环境下更好地服务公众和企业,体现信息时代对顾客需求的响应性。本文从提供什么公共服务、由谁提供以及怎样提供的层面,从政府职能转换、事权财权匹配及绩效管理角度给出一个基于电子政府的分析框架。

关键词：电子政府公共服务财政系统框架

高新技术企业认定政策的创新增量效应及作用机制

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科研管理 2020年第8期41卷 135-141页

作者：徐军玲刘莉华中师范大学公共管理学院湖北武汉430079 中国人民银行南平市中心支行福建南平353000

以湖北2015—2017年新三板年报披露的463家公司数据,从信号传递与股权集中度的调节角度,运用“倾向得分匹配”方法,评估了高新技术企业认定政策的创新增量效应及其作用机制。实证发现:①高新技术企业认定政策能有效激励产出增量,策略性... 详细信息

以湖北2015—2017年新三板年报披露的463家公司数据,从信号传递与股权集中度的调节角度,运用“倾向得分匹配”方法,评估了高新技术企业认定政策的创新增量效应及其作用机制。实证发现:①高新技术企业认定政策能有效激励产出增量,策略性创新激励效应大于实质性创新激励效应;②信号传递的调节作用存在异质性。金融支撑体系对认定政策的投入增量和产出增量效应具有负向调节作用,股权流通性对认定政策的产出增量效应具有正向调节作用;③股权集中度对认定政策的产出增量效应具有负向调节作用。研究结果从投入与产出增量视角丰富了创新激励影响因素研究的文献,并为高新技术企业认证的政策完善提供了实证指导。

关键词：高新技术企业认定增量效应信号传递股权集中度