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Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)最新文献

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DOKMF: Distributed Ontology-Based Knowledge Management Framework DOKMF:分布式本体知识管理框架
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.259
Guangming Wang, Lu Yang
{"title":"DOKMF: Distributed Ontology-Based Knowledge Management Framework","authors":"Guangming Wang, Lu Yang","doi":"10.1109/FSKD.2007.259","DOIUrl":"https://doi.org/10.1109/FSKD.2007.259","url":null,"abstract":"This paper proposes a distributed ontology-based knowledge management framework-DOKMF. An autonomous organization unit is reified as a knowledge node, and virtual communities established according to interests are reified as knowledge communities with some semantic synergy. Global ontology provides a basic glossary of terms and relationships between terms in the domain. Local ontology organizes context-based local knowledge according to local systems. The mappings based on the context address issues of querying and collisions between different local ontologies by a multi- similarities strategy process. This distributed ontology-based design provides the members of a virtual community with more flexible, efficient, adaptable, semantic-based and intelligent knowledge management services.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127354045","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: 1
ApproxMGMSP: A Scalable Method of Mining Approximate Multidimensional Sequential Patterns on Distributed System ApproxMGMSP:一种可扩展的分布式系统中近似多维序列模式挖掘方法
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.192
Changhai Zhang, Kong-fa Hu, Zhuxi Chen, Ling Chen, Yisheng Dong
{"title":"ApproxMGMSP: A Scalable Method of Mining Approximate Multidimensional Sequential Patterns on Distributed System","authors":"Changhai Zhang, Kong-fa Hu, Zhuxi Chen, Ling Chen, Yisheng Dong","doi":"10.1109/FSKD.2007.192","DOIUrl":"https://doi.org/10.1109/FSKD.2007.192","url":null,"abstract":"We present a scalable and effective algorithm called ApproxMGMSP (Approximate Mining of Global Multidimensional Sequential Patterns) to solve the problem of mining the multidimensional sequential patterns for large databases in the distributed environment. Our method differs from previous related works of mining multidimensional patterns on distributed system. The main difference is that an approximate mining method is used in large multidimensional sequence database firstly. In this paper, to convert the mining on the multidimensional sequential patterns to sequential patterns, the multidimensional information is embedded into the corresponding sequences. Then the sequences are clustered, summarized, and analyzed on the distributed sites, and the local patterns could be obtained by the effective approximate sequential pattern mining method. Finally, the global multidimensional sequential patterns could be quickly mined by high vote sequential pattern model after collecting all the local patterns on one site. Both the theories and the experiments indicate that this method could simplify the problem of mining the multidimensional sequential patterns and avoid mining the redundant information. The global sequential patterns could be obtained effectively by the scalable method after reducing the cost of communication.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130109826","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: 15
A Sub-pixel Multifractal Method for the Image Segmentation 一种亚像素多重分形图像分割方法
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.126
G. Wang, Liang Xiao, Anzhi He
{"title":"A Sub-pixel Multifractal Method for the Image Segmentation","authors":"G. Wang, Liang Xiao, Anzhi He","doi":"10.1109/FSKD.2007.126","DOIUrl":"https://doi.org/10.1109/FSKD.2007.126","url":null,"abstract":"The framework of image segmentation based on the sub-pixel multifractal measure (SPMM) is presented in this paper. A more precise singularity exponent distribution in the image can be obtained based on the SPMM. According to the singularity exponents and their statistical properties, the image can be decomposed into a series of sets with different physical characteristics automatically and easily. Moreover, the most singular manifold can be interpreted as the set from which energy is injected in the flow to the other fractal sets. The simulation results show that the SPMM has higher quality factor in the image edge detection.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"44 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128916740","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: 1
Dynamic Knowledge Inference and Learning of Fuzzy Petri Net Expert System Based on Self-Adaptation Learning Techniques 基于自适应学习技术的模糊Petri网专家系统动态知识推理与学习
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.263
Zipeng Zhang, Shuqing Wang, Suyi Liu
{"title":"Dynamic Knowledge Inference and Learning of Fuzzy Petri Net Expert System Based on Self-Adaptation Learning Techniques","authors":"Zipeng Zhang, Shuqing Wang, Suyi Liu","doi":"10.1109/FSKD.2007.263","DOIUrl":"https://doi.org/10.1109/FSKD.2007.263","url":null,"abstract":"It is rather limited for fuzzy production rules to describe the vague and modified knowledge of expert system, an automatic fuzzy reasoning and learning framework based on fuzzy Petri net are presented for design a dynamic expert knowledge system in this paper. Fuzzy Petri net may describe the relative degree of each proposition in the antecedent contributing to the consequent accurately. In order to reason and learn expediently, FPN without loop is transformed into hierarchy model and continuous functions to approximate transition firing and fuzzy reasoning. The self-adaptation learning techniques based on back-propagation are used to learn and train parameters of fuzzy production rules of FPN. Simulation experiment shows that the improved adaptive learning techniques can make rule parameters obtain optimal or at least nearly optimal convergence rapidly.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129019549","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: 3
An Intelligent TCM Diagnostic System Based on Intuitionistic Fuzzy Set 基于直觉模糊集的中医智能诊断系统
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.169
Meihong Wu, Changle Zhou, Kunhui Lin
{"title":"An Intelligent TCM Diagnostic System Based on Intuitionistic Fuzzy Set","authors":"Meihong Wu, Changle Zhou, Kunhui Lin","doi":"10.1109/FSKD.2007.169","DOIUrl":"https://doi.org/10.1109/FSKD.2007.169","url":null,"abstract":"This paper proposes an intelligent traditional Chinese medical diagnostic system based on multi-agent system. In this system we also introduce an intelligent fuzzy diagnostic model based on intuitionistic fuzzy set theory according to the characteristics of traditional Chinese medicine, which realize intelligent diagnosis by modeling medical diagnosis rules via fuzzy relations, finally we propose a new approach for similarity measure between the intuitionistic fuzzy sets of syndromes.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122364063","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: 6
A Convex Combination Approach for the Weights of Interval Fuzzy Preference Relation 区间模糊偏好关系权值的凸组合方法
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.13
Ji-bin Lan, Fang Liu
{"title":"A Convex Combination Approach for the Weights of Interval Fuzzy Preference Relation","authors":"Ji-bin Lan, Fang Liu","doi":"10.1109/FSKD.2007.13","DOIUrl":"https://doi.org/10.1109/FSKD.2007.13","url":null,"abstract":"The weights of interval fuzzy preference relation generated in the analytic hierarchy process are investigated. Making use of a convex combination method, a family of real fuzzy preference relations are constructed. The aggregation of the weights of the family of real fuzzy preference relations is considered as the weights of interval fuzzy preference relation. In order to make any weight vector of the family of real fuzzy preference relations reliable, the sufficient and necessary conditions of their consistency and weak transitivity are given. When they are inconsistent, the method of repairing them to reach weak transitivity is also proposed. A numerical example is given to illustrate the validity and practicality of the developed methods.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"51 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130772755","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: 4
The Research on Hierarchical Risk Element Transmission Theory Based on Fuzzy Theory and Data Mining 基于模糊理论和数据挖掘的分层风险要素传递理论研究
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.583
Cunbin Li, Jianjun Wang
{"title":"The Research on Hierarchical Risk Element Transmission Theory Based on Fuzzy Theory and Data Mining","authors":"Cunbin Li, Jianjun Wang","doi":"10.1109/FSKD.2007.583","DOIUrl":"https://doi.org/10.1109/FSKD.2007.583","url":null,"abstract":"The traditional analytic hierarchy process (AHP) models are usually based on the precise data and it is difficult to handle the uncertainty evaluation problems. Currently, the studies of AHP models usually evaluate the uncertainty problems based on fuzzy or interval number theory but the evaluation results can not provide complete decision information to the decision makers satisfactorily. Hierarchical risk element transmission (HRET) theory is a new idea of the uncertain evaluation problems. This paper constructs a frame of HRET, at first, fuzzy extended analytic hierarchy process (FEAHP) is used to decide the weight of HRET model, then the triangle fuzzy numbers which is used to solve HRET problems is acquired by the data mining technology based on history data. By doing this, the concluded results can provide more complete information to the decision makers with the consideration of the risk.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132392632","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
Topological Properties in Covering-Based Rough Sets 基于覆盖粗糙集的拓扑性质
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.592
William Zhu, Fei-Yue Wang
{"title":"Topological Properties in Covering-Based Rough Sets","authors":"William Zhu, Fei-Yue Wang","doi":"10.1109/FSKD.2007.592","DOIUrl":"https://doi.org/10.1109/FSKD.2007.592","url":null,"abstract":"In covering setting, there are five types of rough set models in literature, but only one type of them has been studied from the point of topological view. In this paper, we address the topological properties in the other four types of covering-based rough sets; especially we present the conditions under which lower approximation operations become interior operators and the conditions under which the upper approximation operations become closure operators.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132491147","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: 21
Learning Locality Discriminating Indexing for Text Categorization 学习文本分类的位置判别索引
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.383
Jiani Hu, Weihong Deng, Jun Guo, Weiran Xu
{"title":"Learning Locality Discriminating Indexing for Text Categorization","authors":"Jiani Hu, Weihong Deng, Jun Guo, Weiran Xu","doi":"10.1109/FSKD.2007.383","DOIUrl":"https://doi.org/10.1109/FSKD.2007.383","url":null,"abstract":"This paper introduces a locality discriminating indexing (LDI) algorithm for text categorization. The LDI algorithm offers a manifold way of discriminant analysis. Based on the hypothesis that samples from different classes reside in class-specific manifold structures, the algorithm depicts the manifold structures by a nearest-native graph and a invader graphs. And a new locality discriminant criterion is proposed, which best preserves the within-class local structures while suppresses the between-class overlap. Using the notion of the Laplacian of the graphs, the LDI algorithm finds the optimal linear transformation by solving the generalized eigenvalue problem. The feasibility of the LDI algorithm has been successfully tested in text categorization using 20NG and Reuters-21578 databases. Experiment results show LDI is an effective technique for document modeling and representations for classification.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132866831","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: 1
Forecasting Stock Price Index Using Fuzzy Time-Series Based on Rough Set 基于粗糙集的模糊时间序列股票价格指数预测
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Pub Date : 2007-08-24 DOI: 10.1109/FSKD.2007.296
Ching-Hsue Cheng, H. Teoh, Tai-liang Chen
{"title":"Forecasting Stock Price Index Using Fuzzy Time-Series Based on Rough Set","authors":"Ching-Hsue Cheng, H. Teoh, Tai-liang Chen","doi":"10.1109/FSKD.2007.296","DOIUrl":"https://doi.org/10.1109/FSKD.2007.296","url":null,"abstract":"Fuzzy time-series have been utilized to make predictions in various areas such as stock price forecasting, academic enrollments and weather. In the forecasting processes, Fuzzy Logical Relation (FLR) is the one of critical factors to influence forecasting accuracy. Therefore, in this paper, we propose a new fuzzy time-series method, which employs rough set theory to mine FLR in time-series and the adaptive expectations model to tune forecasting results. In the empirical analysis, we use a ten-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) closing prices as experimental datasets and two fuzzy time-series methods, Chen's (1996) and Yu's (2004) methods, as comparisons models. The experimental results shows that propose method outperforms the listing methods.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127915611","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
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