检索结果-内蒙古大学图书馆

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Bo Yang Da-You Liu Open Symbol Computation and Knowledge Engineering Laboratory of State Education Department Jilin University Changchun China Jilin University Changchun Jilin CN Coll. of Comput. Sci. & Technol. Jilin Univ. Changchun China

Community structure is an important property of networks. Being able to identify communities can provide invaluable help in exploiting and understanding both social and non-social networks. Several algorithms have been developed up till now. However all these algorithms can work well only with small or moderate networks with vertexes of order 10/sup 4/. Additionally, all existing algorithms are off-line and can not work well with highly dynamic networks such as Web, in which Web pages are updated frequently every day. When the already clustered network is updated, the entire network including original and incremental parts has to be recalculated, even only slight changes involved. To address this problem we develop an incremental algorithm which allows for detecting community structure in large-scale and dynamic networks. Based on the community structure it detect previously our algorithm takes little time to reclassify the entire network including both original and incremental parts. Furthermore, our algorithm is faster than most existing algorithms such as Girvan and Newman's algorithm and its improved versions. Also our algorithm can help to visualize these community structures in network and provide a new approach to research the evolving process of dynamic networks.

关键词： Intelligent networks Clustering algorithms Partitioning algorithms Social network services Machine learning algorithms Computer networks Visualization Web sites Biochemistry Educational institutions

来源：评论

学校读者我要写书评

暂无评论

A directional algorithm based on shape context for 3D point pattern matching

引用

Journal of computational Information Systems 2015年第7期11卷 2355-2365页

作者： Pang, Kuo Liang, Yanchun Zhou, You Wang, Kangping Wang, Shu Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun China Department of Computer Science and Technology Zhuhai College of Jilin University Zhuhai China

Point pattern matching is the basis of image recognition and computer vision. Point pattern matching in three dimensional space with the presence of noise and outlier is an important research focus. In this paper, we present a novel method for point pattern matching base on shape context. Particularly, we aim to find robust feature points to determine the positive direction of the point set for three dimensional rotation. At the same time, we improve the feature extraction and similarity measurement, and then combine with bipartite map matching. Comparative experiments on both synthetic point sets and real data sets demonstrate that the proposed algorithm is effective and robust. ©, 2015, Binary Information Press. All right reserved.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Describing the semantic relation of the deep web query interfaces using ontology extended LAV

Journal of Software

引用

Journal of Software 2010年第1期5卷 89-98页

作者： Liang, Hao Zuo, Wan-Li Ren, Fei Department of Computer Science and Technology Jilin University Jilin Changchun China Department of Information Changchun Taxation College Jilin Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema. © 2010 ACADEMY PUBLISHER.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Operon Prediction by Markov Clustering

Operon Prediction by Markov Clustering

引用

2011·国际基因组学大会

作者： Wei Du Zhongbo Cao Yan Wang Enrico Blanzieri Chen Zhang Yanchun Liang College of Mathematics Jilin University Changchun 130012 China Department of Information and Communication Technology University of Trento Povo 38050 Italy College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

来源：评论

学校读者我要写书评

暂无评论

An Efficient Method for Very Large Scale Out-of-Core Terrain Visualization

An Efficient Method for Very Large Scale Out-of-Core Terrain...

引用

International Conference on Artificial Reality and Telexistence (ICAT)

作者： Huijie Zhang Jigui Sun Haihong Yu Changsong Qi College of Computer Science Northeast Normal University China College of Computer Science and Technology Jilin University China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education China

Large scale terrain visualization with high- resolution has an increasing demand in many research fields. To realize the efficient rendering of terrain, this paper presents an out-of-core terrain visualization method based on multi-resolution storage techniques. In external memory, the terrain data set is subdivided from top to bottom to build a multi-resolution hierarchical structure based on a quad-tree. The hierarchical structure can decimate the elevation data that must be loaded into internal memory. Thus it can improve the efficiency of I/O access greatly. Moreover, in order to implement rapid data retrieval of the real time terrain flyover, an efficient indexing algorithm is proposed, in which those nodes in the hierarchical structure will be divided into several clusters in terms of the similarities of static error and the closed space constraint. In addition, a method for crack-free is also proposed here. The comprehensive experiment conducted on the GTOP30 data set shows that this approach outperforms the Block and the Hierarchy algorithms in the both ways of efficiency and simplification ratio.

关键词： Large-scale systems Clustering algorithms Information retrieval Educational institutions Computer science Data visualization Educational technology Costs Data structures Partitioning algorithms

来源：评论

学校读者我要写书评

暂无评论

IInfoGAN: Improved Information Maximizing Generative Adversarial Networks

IInfoGAN: Improved Information Maximizing Generative Adversa...

引用

International Conference on Mechanical, Control and Computer engineering (ICMCCE)

作者： Yan Wang Pujia Wang Boyang Sun Kai He Lan Huang School of Artificial Intelligence Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering College of Computer Science and Technology Jilin University Ministry of Education Changchun China

Generative Adversarial Networks (GANs) have achieved huge success in some unsupervised learning fields. There is no doubt that clustering takes a lot of weight in unsupervised algorithm. And in this paper, we raise the Improved Information Maximizing Generative Adversarial Networks (IInfoGAN) algorithm for learning discriminative classifiers from unlabeled data. The basis of our method is an math function that contains the Mutual Information (MI) and Cross Entropy of the observed examples and their predicted classification category distribution, thus enhancing the robustness of the classifier to adversarial generative models. Experiments show that the interpretable representation learned by IInfoGAN is competitive with the representation learned by existing unsupervised methods.

关键词： Training Time series analysis Clustering algorithms Predictive models Generative adversarial networks Prediction algorithms Entropy

来源：评论

学校读者我要写书评

暂无评论

Automatic table integration by domain-specific ontology

International Journal of Digital Content Technology and its ...

引用

International Journal of Digital Content Technology and its Applications 2011年第1期5卷 218-225页

作者： Kerui, Chen Jinchao, Zhao Wanli, Zuo Fengling, He Yongheng, Chen College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and knowledge Engineering of the Ministry of Education Changchun China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China

Deep web could automatically produce web pages according to the query criteria of users. The report found most query result page store data information using table form. knowledge management, information retrieval, Web mining, abstract extraction and so on were benefited from automatically understanding of table forms. The study web forms on the web information extraction and integration have important significance. This paper proposed a domain-specific ontology based strategy for integration tables, and this method could independent the structure of table. Experimental results confirm that this method could effectively improve the accuracy of integration.

关键词： Integration

来源：评论

学校读者我要写书评

暂无评论

Mining data records based on ontology evolution for deep web

Mining data records based on ontology evolution for deep web

引用

International Conference on Computer engineering and Technology, ICCET

作者： Wen Zhang Kerui Chen Fan Zhang College of Information Engineering Zhongzhou University Zhengzhou China College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)9781424463473;9781424463497;9781424463503

Currently, the research for the extraction of information in deep web is pretty active. Although many researchers already adopted ontology in the data extraction, many problems still exist. This paper proposed an ontology evolution based method for mining in the data area. Not only will this method solve the problem when the website only consists of one record, but it also can identify he meaning of data that has no labels. With the evolution of ontology, the extraction of data records is being more accurate. Experiments indicate that this method could improve the accuracy and efficiency of data extraction.

关键词： Data mining Ontologies Entropy Educational institutions knowledge engineering Web pages Data engineering Random processes Computer science Educational technology

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous deep web data extraction using ontology evolution

引用

Journal of Convergence Information Technology 2010年第8期5卷 23-23页

作者： Chen, Kerui Zhao, Jinchao Zuo, Wanli He, Fengling Chen, Yongheng College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China

This paper proposed a complex ontology evolution based method of extracting data, and also completely designed an extraction system, which consists of four important components: Resolver, Extractor, Consolidator and the ontology construction components. The system gives priority to the construction of mini-ontology. When the user submits query keywords to the deep web query interface, the returned result will pass through the prior three components;after that, the final execution result will be returned to user in a unified form. This paper adopted an extraction method that is different from the general ontology extraction. More specifically, the ontology used in extraction here is dynamic evolution, which can adapt various data source better. Experimental results proved that this method could effectively extract the data in the query result pages.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Image annotation refinement using dynamic weighted voting based on mutual information

Journal of Software

引用

Journal of Software 2011年第11 SPEC. ISSUE期6卷 2239-2246页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Institute of Computer Graphics and Image Processing Dalian Nationalities University Dalian China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

Automatic image annotation is a promising solution to narrow the semantic gap between low-level content and high-level semantic concept, which has been an active research area in the fields of image retrieval, pattern recognition, and machine learning. However, even the most dedicated annotation algorithms are often unsatisfactory. Image annotation refinement has attracted much more attention recently. In this paper, a novel refinement algorithm using dynamic voting based on mutual information is proposed. Unlike the traditional refinement algorithm, the proposed algorithm adopts dynamic weighted voting to measure the dependence between the candidate annotations, which not only permits that the annotations with higher probabilities deny the annotations with lower probabilities, but also permits that the annotations with lower probabilities deny the annotations with higher probabilities. The proposed refinement algorithm adopts progressive method instead of iterative, which can significantly decrease the time cost of refining annotations. In order to further improve efficiency without sacrificing precision, we propose the block-based normalized cut algorithm to segment image. Experiments conducted on standard Washington Ground Truth Image Database demonstrate the effectiveness and efficiency of our proposed approach for refining image annotations. © 2011 ACADEMY PUBLISHER.

关键词： Image annotation

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：