2007 IEEE International Conference on Granular Computing (GRC 2007)最新文献

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Autonomic Learning Model and Algorithm Based on DFL 基于DFL的自主学习模型与算法
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.71
Jing Wang, Fanzhang Li
{"title":"Autonomic Learning Model and Algorithm Based on DFL","authors":"Jing Wang, Fanzhang Li","doi":"10.1109/GrC.2007.71","DOIUrl":"https://doi.org/10.1109/GrC.2007.71","url":null,"abstract":"Autonomic learning (AL) refers to an inner mechanism of self-directed learning integrated by learner's attitude, capability and learning strategy. AL usually means active, self-conscious and independent learning, which is opposite to the type of passive, mechanical or receptive learning. AL has always been a hot issue of machine learning research. In this paper, based on the theory of dynamic fuzzy logic (DFL), autonomic learning model and algorithm are developed, which provide a theoretical basis for the people to solve this type of problem. Simulation results illustrate the efficiency of this autonomic learning method.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125546366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Object Recognition Architecture Using Distributed and Parallel Computing with Collaborator 基于分布式和并行计算的协同目标识别体系结构
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.94
Junhee Lee, Sue J. Lee, Yeonchool Park, Sukhan Lee
{"title":"Object Recognition Architecture Using Distributed and Parallel Computing with Collaborator","authors":"Junhee Lee, Sue J. Lee, Yeonchool Park, Sukhan Lee","doi":"10.1109/GrC.2007.94","DOIUrl":"https://doi.org/10.1109/GrC.2007.94","url":null,"abstract":"These days, object recognition is regarded as a sufficient condition for essential requirements of intelligent service robot. Under such demands, object recognition's algorithms and its methods have been increasing in complexity along with the increase of computational ability. Despite these developments, object recognition still consumes many computational resources, which impede total time throughput drop. The purpose of this paper is to suggest an object recognition software architecture, which reduces time throughput by applying concepts of 'Component based approach' and COMET (Concurrent Object Modeling and architectural design mEThod), a computational efficiency improvement method. In COMET, the component based approach reduces total time throughput by supporting dynamic distributed and parallel processing. To enable these computations, surplus computational resources of nearby collaborator robot can be used for distributed computing by SHAGE, which is a component management framework based on COMET. Using SHAGE, in order to connect physical operation among components, software function module should be a componentized component defined by 'COMET component design guideline'. This paper componentizes the object recognition software function modules via this guideline, and shows the object recognition architecture as a connected relationship among these components. The experimental results show a maximum of 42% performance improvement compared to the original multi-feature evidence recognition framework.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130005543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 25
MGRS in Incomplete Information Systems 不完全信息系统中的MGRS
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.10
Y. Qian, Jiye Liang, C. Dang
{"title":"MGRS in Incomplete Information Systems","authors":"Y. Qian, Jiye Liang, C. Dang","doi":"10.1109/GrC.2007.10","DOIUrl":"https://doi.org/10.1109/GrC.2007.10","url":null,"abstract":"The original rough set model is concerned primarily with the approximation of sets described by single binary relation on the universe. In the view of granular computing, classical rough set theory is researched by single granulation. The article extends the rough set model based on tolerance relation to incomplete rough set model based on multi-granulations, where the set approximations are defined by using multi tolerance relations on the universe. Its some basic mathematical properties are investigated as well. It is shown that some properties of rough set model based on tolerance relation are special instances of this new model, the approximation measure of a target concept described by using multi-granulations is always better than by using single granulation, which is suitable for describing more accurately the concept and solving problem according to user requirement in incomplete information systems.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128018773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 39
Mining Diagnostic Taxonomy and Diagnostic Rules for Multi-Stage Medical Diagnosis from Hospital Clinical Data 从医院临床数据中挖掘多阶段医学诊断的诊断分类和诊断规则
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.128
S. Tsumoto
{"title":"Mining Diagnostic Taxonomy and Diagnostic Rules for Multi-Stage Medical Diagnosis from Hospital Clinical Data","authors":"S. Tsumoto","doi":"10.1109/GrC.2007.128","DOIUrl":"https://doi.org/10.1109/GrC.2007.128","url":null,"abstract":"Experts' reasoning selects the final diagnosis from many candidates by using hierarchical differential diagnosis. In other words, candidates give a sophisticated hiearchical taxonomy, usually described as a tree. In this paper, the characteristics of experts' rules are closely examined from the viewpoint of hierarchical decision steps and and a new approach to rule mining with extraction of diagnostic taxonomy from medical datasets is introduced. The key elements of this approach are calculation of the characterization set of each decision attribute (a given class) and one of the similarities between characterization sets. From the relations between similarities, tree-based taxonomy is obtained, which includes enough information for hierarchical diagnosis. The proposed method was evaluated on three medical datasets, the experimental results of which show that induced rules correctly represent experts' decision processes.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130781513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Grid-Based Service Creation for Next-Generation Networks 下一代网络基于网格的服务创建
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.102
Z. Liu
{"title":"Grid-Based Service Creation for Next-Generation Networks","authors":"Z. Liu","doi":"10.1109/GrC.2007.102","DOIUrl":"https://doi.org/10.1109/GrC.2007.102","url":null,"abstract":"Compared with traditional telecommunication networks, service creation in next-generation networks (NGN) gives rise to new opportunities and challenges. In this paper, we propose a NGN service creation model SECOM and its two criteria, that is, OPEN and INTEGRATION of network capabilities. OPEN enables a uniform access to heterogeneous network capabilities, while INTEGRATION enables loose-coupled distributed open services to be converged. We implement a prototype ParlayGS based on Parlay and open grid services architecture (OGSA), which implement OPEN and INTEGRATION criteria all in one. Simulations were made to illustrate and verify the open and integration aspects of ParlayGS on creating services. Our efforts show that SECOM and its prototype ParlayGS are valid and effective, which not only supports new complex services spanning heterogeneous networks, but also enables flexible and rapid ways for service interconnection with lower protocol conversion complexity.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130904759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research of Web Pages Categorization 网页分类的研究
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.122
Zhongda Lin, Kun Deng, Yanfen Hong
{"title":"Research of Web Pages Categorization","authors":"Zhongda Lin, Kun Deng, Yanfen Hong","doi":"10.1109/GrC.2007.122","DOIUrl":"https://doi.org/10.1109/GrC.2007.122","url":null,"abstract":"The Web is a huge repository of information and there is a need for categorizing Web pages to facilitate the indexing, search, and retrieval of pages. In this paper, we discuss several issues related to automated classification of web pages, especially classification of textual web pages. We analyze features selection and categorization algorithms of web pages and give some suggestions for web pages categorization.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121270158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Algorithms for Different Approximations in Incomplete Information Systems with Maximal Compatible Classes as Primitive Granules 以最大相容类为原粒的不完全信息系统的不同逼近算法
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.58
Chen Wu, Xiaohua Hu, Zhoujun Li, Xiaohua Zhou, Palakorn Achananuparp
{"title":"Algorithms for Different Approximations in Incomplete Information Systems with Maximal Compatible Classes as Primitive Granules","authors":"Chen Wu, Xiaohua Hu, Zhoujun Li, Xiaohua Zhou, Palakorn Achananuparp","doi":"10.1109/GrC.2007.58","DOIUrl":"https://doi.org/10.1109/GrC.2007.58","url":null,"abstract":"This paper proposes some expanded rough set models with maximal compatible classes as primitive granules, introduces two new granules for extending rough set model, and designs algorithms to solve maximal compatible classes, to find the lower and upper approximations according to the newly granules, to compute reducts and minimal reducts with attribute significance. It also verifies the validity of algorithms by examples. These provide an important and implemental theoretical base for rough set theory to deal with problems in incomplete information systems.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125456310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Privacy Preserving Collaborative Filtering Using Data Obfuscation 利用数据混淆保护隐私的协同过滤
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.133
Rupa Parameswaran, D. Blough
{"title":"Privacy Preserving Collaborative Filtering Using Data Obfuscation","authors":"Rupa Parameswaran, D. Blough","doi":"10.1109/GrC.2007.133","DOIUrl":"https://doi.org/10.1109/GrC.2007.133","url":null,"abstract":"Collaborative filtering (CF) systems are being widely used in E-commerce applications to provide recommendations to users regarding products that might be of interest to them. The prediction accuracy of these systems is dependent on the size and accuracy of the data provided by users. However, the lack of sufficient guidelines governing the use and distribution of user data raises concerns over individual privacy. Users often provide the minimal information that is required for accessing these E-commerce services. In this paper, we propose a framework for obfuscating sensitive information in such a way that it protects individual privacy and also preserves the information content required for collaborative filtering. An experimental evaluation of the performance of different CF systems on the obfuscated data proves that the proposed technique for privacy preservation does not impact the accuracy of the predictions. The proposed framework also makes it possible for multiple E-commerce sites to share data in a privacy preserving manner. Problems such as the cold-start scenario faced by new E-commerce vendors, and biased results due to insufficient users, are resolved by using a shared CF server. We describe a centralized CF server model in which a centralized CF server makes recommendations by consolidating the information received from multiple sources.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127581346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 59
A New Scheme of EEG Signals Processing in Brain-Computer Interface Systems 脑机接口系统中脑电信号处理的新方案
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.149
M. Esmaeili, Mohamad H. Jabalameli, Zeinab Moghadam
{"title":"A New Scheme of EEG Signals Processing in Brain-Computer Interface Systems","authors":"M. Esmaeili, Mohamad H. Jabalameli, Zeinab Moghadam","doi":"10.1109/GrC.2007.149","DOIUrl":"https://doi.org/10.1109/GrC.2007.149","url":null,"abstract":"In this paper, dynamic synapse neural network (DSNN) has been applied to perform EEG signal recognition task. The wavelet packet transform is applied to the EEG signal in order to decompose it into frequency sub-bands, before being introduced to the neural network. In this study we have applied a genetic algorithm (GA) learning method with different fitness functions to optimize the neural network. The advantage of the GA method is that it facilitates finding of a semi-optimal parameter set in the search space domain. The network has been testes for EEG signals tat are provided from BCI Competition 2003 and the results show the power of DSNN in processing of noisy nature signals as EEG signals.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130523661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Rough Set Approximations Based on Random Sets 基于随机集的粗糙集逼近
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.22
Weizhi Wu
{"title":"Rough Set Approximations Based on Random Sets","authors":"Weizhi Wu","doi":"10.1109/GrC.2007.22","DOIUrl":"https://doi.org/10.1109/GrC.2007.22","url":null,"abstract":"In this paper, the concept of a random rough set which includes the mechanisms of numeric and non-numeric aspects of uncertain knowledge is introduced. It is shown that for any belief structure and its inducing belief and plausibility measures there exists a random approximation space such that the associated lower and upper probabilities are respectively the given belief and plausibility measures, and vice versa. And for a random approximation space generated from a totally random set, its inducing lower and upper probabilities are respectively necessity and possibility measures.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128449775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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