检索结果-内蒙古大学图书馆

International Symposiums on information processing (ISIP)

作者： Zhiming Cui Pengpeng Zhao Wei Fang Chao Lin The Institute of Intelligent Information Processing and Application China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9781424430536;9780769531519

The next generation of the Web, called Semantic Web, has to improve the Web with semantic page annotations to enable knowledge-level querying and searches. However, manual construction of these ontologies is a time consuming and difficult task. In this paper, we describe an automatic extraction method that learns domain ontologies for semantic web from deep web. Our approach first learns a base ontology from deep web query interfaces, then grows the current ontology by probing the sources and discovering additional concepts and instances from the result pages. We have evaluated our approach in several real-world domains. Preliminary results indicate that the proposed extraction method discovers concepts and instances with high accuracy.

关键词： Wrapping Ontologies Semantic Web information processing Databases Knowledge engineering Chaos Application software Laboratories Machine learning

来源：评论

学校读者我要写书评

暂无评论

Tree Kernel-Based Semantic Relation Extraction Using Unified Dynamic Relation Tree

Tree Kernel-Based Semantic Relation Extraction Using Unified...

引用

International Conference on Advanced Language processing and Web information technology (ALPIT)

作者： Longhua Qian Guodong Zhou Fang Kong Qiaomin Zhu Peide Qian Jiangsu Provincial Key Laboratory for Computer Information Processing Technology School of Computer Science and Technology Soochow University Suzhou China

This paper proposes a unified dynamic relation tree (DRT) span for tree kernel-based semantic relation extraction between entity names. The basic idea is to apply a variety of linguistics-driven rules to dynamically prune out noisy information from a syntactic parse tree and include necessary contextual information. In addition, different kinds of entity-related semantic information are unified into the syntactic parse tree. Evaluation on the ACE RDC 2004 corpus shows that the unified DRT span outperforms other widely-used tree spans, and our system achieves comparable performance with the state-of-the-art kernel-based ones. This indicates that our method can not only well model the structured syntactic information but also effectively capture entity-related semantic information.

关键词： Artificial neural networks Data mining Feature extraction Kernel Cities and towns Noise measurement Joining processes

来源：评论

学校读者我要写书评

暂无评论

Multivariate classification of deep web sources based on maximum entropy model

引用

Journal of Computational information Systems 2008年第3期4卷 1093-1100页

作者： Huang, Li Zhao, Pengpeng Cui, Zhiming Wei, Fang Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China

With the fast development of World Wide Web, the quantity of web information is increasing in an unprecedented pace, a great many of which are generated dynamically from background databases, and can't be indexed by traditional search engine, so we call them Deep Web. For the heterogeneous and dynamic features of Deep Web sources, classifying the Deep Web source by domain effectively is a significant precondition of Deep Web sources integration. In this paper, we consider the visible features of Deep Web and Maximum Entropy approach, and then on the basis of binary classification, we propose a new multivariate classification approach based on Maximum Entropy towards Deep Web sources. In addition, we propose a Feedback algorithm to improve the accuracy of classification. An experimental evaluation over real Web data shows that, our approach could provide an effective and general solution to the multivariate classification of Deep Web sources.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Chaotic time series forecast modeling based on biased wavelet neural network

Chaotic time series forecast modeling based on biased wavele...

引用

International Conference on computer Science and Software Engineering, CSSE 2008

作者： Fang, Liu Desheng, Jiang Fangpeng, Qiu Jianzhong, Zhou School of Computer Science and Technology Wuhan University of Technology Key Laboratory of Fiber Optic Sensing Technology Information Processing of Ministry of Education Wuhan University of Technology School of Management Huazhong University of Science and Technology School of Hydropower and Information Engineering Huazhong University of Science and Technology

ISBN: (纸本)9780769533360

Chaos and artificial neural networks have been providing a new rout for investigating the complicated nonlinear time series. As the traditional neural networks are easy to get slow convergence and produce large redundancy which might consequently bring low efficiency, the biased wavelet neural networks is employed to build chaotic time series forecasting. Efforts are also made to assess the forecast modeling process, characteristics and key coefficients selection. Together with the phase space reconstruction theory, this paper discusses the application to month inflow runoff time series, which shows that the presented method is feasible and obtains satisfying forecast precisions. © 2008 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Implementation of data-exchanging system based on message oriented middleware in agricultural website

引用

WSEAS Transactions on computers 2008年第6期7卷 620-629页

作者： Zhang, Xiaoshuan Wu, Qinghua Tian, Dong Zhao, Ming Xiaoshuan, Zhang College of Information and Electrical Engineering China Agricultural University Beijing 100083 China Jiangsu Provincial Key Laboratory Computer Information Processing Technology Suzhou China

With the startup of the Golden Agriculture Project, the step of being-information of agriculture is becoming rapid. And the transformation and share of data is indispensable to the being-information of agriculture. How to implement data combination, data transformation and data receiving applications are the important means to complete the information share safely and enhance the efficiency. The paper starts with searching of methods to implement data interchange, and introduce some of the methods, points of the techniques, etc. Basing on this, the paper also introduces the detail requirement analyses, system design and detail implementation of the system. According to the requirement and trait of the project, a data interchange system is researched and completed. And a data interchange model based on message-oriented middleware (MOM) is presented in this paper, which builds a middleware between the province and the ministry taking part in data interchange. The system has traits as follows: 1. keeping the data safe and credible while it is transformed. 2. having excellent transplantable and applied capability. 3. doesn't need intervention of workman in the process of data interchange. 4. applying the data interchange between databases of different structure. 5. being simple to be developed and applied. MOM TongLink/Q offers interfaces for application development, and it completes the data transformation through the internet. The integration adapters developed do the data management, which are developed based on the Frame for Applications Integration TongIntegrator. This method offers a new approach to resolve the question of data interchange. Now the system has been successfully applied in the data interchange project of Ministry of Agriculture.

关键词： Electronic data interchange

来源：评论

学校读者我要写书评

暂无评论

DNA computing model based on lab-on-a-chip and its application on solving the timetabling problem

引用

Progress in Natural Science:Materials International 2008年第5期18卷 633-637页

作者： Fengyue Zhang a,1, Bo Liu b,1, Wenbin Liu c, Qiang Zhang d a Department of Biomedical Engineering, School of Life Science and technology, Beijing Institute of technology, Beijing 100081, China b Chinese Academy of Inspection and Quarantine, Beijing 100029, China c College of computer Science and Engineering, Wenzhou University, Wenzhou, Zhejiang 325027, China d Liaoning key laboratory of Intelligent information processing, Dalian University, Dalian, Liangning 116622, China Department of Biomedical Engineering School of Life Science and Technology Beijing Institute of Technology Beijing 100081 China Chinese Academy of Inspection and Quarantine Beijing 100029 China College of Computer Science and Engineering Wenzhou University Wenzhou Zhejiang 325027 China Liaoning Key Laboratory of Intelligent Information Processing Dalian University Dalian Liangning 116622 China

The essential characteristic of DNA computation is its massive parallelism in obtaining and managing information. With the develop- ment of molecular biology technique, the eld of DNA computation has made a great progress. By using an advanced biochip technique, laboratory-on-a-chip, a new DNA computing model is presented in the paper to solve a simple timetabling problem, which is a special ver- sion of the optimization problems. It also plays an important role in education and other industries. With a simulated biological experiment, the result suggested that DNA computation with lab-on-a-chip has the potential to solve a real complex timetabling problem.

关键词： DNA computing Timetabling problem Lab-on-a-chip

来源：评论

学校读者我要写书评

暂无评论

Adaptive Shadows Detection Algorithm Based on Gaussian Mixture Model

Adaptive Shadows Detection Algorithm Based on Gaussian Mixtu...

引用

International Symposium on information Science and Engineering, ISISE

作者： Yu-jiao XiaHou Sheng-rong Gong Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China Soochow University Suzhou Jiangsu CN

This paper proposed an adaptive shadows detection algorithm based on Gaussian Mixture Model to improve the performance of video object segmentation. This method takes advantage of luminance weight to model the background of the image and obtains a primary segmentation in CIE Luv color space. In this way, it improves the real-time ability of detection. It also becomes more efficient, comparing with the existing shadow detection algorithms which often need to set the threshold manually or get them through a training process. By using the Gaussian distribution, it is able to realize an adaptive shadow detection. At same time, the authors deal with the noise or the aim points uneven distribution by using horizontal filling and vertical filling. It improves the accuracy of segmentation. The experimental results have shown that this method achieves adaptive shadows detection and has strong robustness, high segmentation accuracy.

关键词： Detection algorithms Clustering algorithms Layout Gaussian distribution Pixel Object segmentation Filling Object detection Streaming media information science

来源：评论

学校读者我要写书评

暂无评论

Nonlinear forecast modeling based on wavelet analysis

Nonlinear forecast modeling based on wavelet analysis

引用

International Conference on computer Science and Software Engineering, CSSE 2008

作者： Liu, Fang Jiang, Desheng Fu, Bo Zhou, Jianzhong School of Computer Science and Technology Wuhan University of Technology China Key Laboratory of Fiber Optic Sensing Technology and Information Processing Ministry of Education Wuhan University of Technology China School of Electrical and Electronic Engineering Hubei University of Technology China School of Hydropower and Information Engineering Huazhong University of Science and Technology China

ISBN: (纸本)9780769533360

System modeling is a complex nonlinear procedure. Traditional methods are easy to get slow convergence and low efficiency. The nonlinear forecast modeling based on wavelet analysis is proposed and used to forecast the change trends of runoff. It inherits the multiresolution capability of wavelets analysis, and with the generalization of forecast modeling, the presented method is applied to annual runoff forecast of Yichang. The simulation performance is compared with that of autoregressive model. It is shown that wavelet analysis is able to find the latent detail information of time series and supply satisfying forecast results under different time scales. © 2008 IEEE.

关键词： Wavelet analysis

来源：评论

学校读者我要写书评

暂无评论

Automated Essay Scoring Using the KNN Algorithm

Automated Essay Scoring Using the KNN Algorithm

引用

International Conference on computer Science and Software Engineering

作者： Li Bin Lu Jun Yao Jian-Min Zhu Qiao-Ming Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9781424439027

The K-Nearest Neighbor (KNN) algorithm for text categorization is applied to CET4 essays. In this paper, each essay is represented by the vector space model (VSM). After removing the stop words, we chose the words, phrases and arguments as features of the essays, and the value of each vector is expressed by the term frequency and inversed document frequency (TF-IDF) weight. The TF and information fain (IG) methods are used to select features by predetermined thresholds. We calculated the similarity of essays with cosine in the KNN algorithm. Experiments on CET4 essays in the Chinese Learner English Corpus (CLEC) show accuracy above 76% is achieved.

关键词： Frequency Text categorization Writing Software algorithms Space technology Machine learning Performance gain computer science Software engineering Laboratories

来源：评论

学校读者我要写书评

暂无评论

An Improved Algorithm of Decision Trees for Streaming Data Based on VFDT

An Improved Algorithm of Decision Trees for Streaming Data B...

引用

International Symposium on information Science and Engineering, ISISE

作者： Feixiong Li Quan Liu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China

Decision tree is a good model of Classification. Recently, there has been much interest in mining streaming data. Because streaming data is large and no limited, it is unpractical that passing the entire data over more than one time. A one pass online algorithm is necessary. One of the most successful algorithms for mining data streams is VFDT(Very Fast Decision Tree).we extend the VFDT system to EVFDT(Efficient-VFDT) in two directions: (1)We present Uneven Interval Numerical Pruning (shortly UINP) approach for efficiently processing numerical attributes. (2)We use naive Bayes classifiers associated with the node to process the samples to detect the outlying samples and reduce the scale of the trees. From the experimental comparison, the two techniques significantly improve the efficiency and the accuracy of decision tree construction on streaming data.

关键词： Decision trees Classification tree analysis Data mining information science Laboratories information processing Buildings Classification algorithms H infinity control Histograms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：