2006 IEEE International Conference on Granular Computing最新文献

{"title":"On structural information similarity measurements","authors":"Jinmao Wei, Shuqin Wang, Wei Zheng, Jing Wang, Junping You, Jie Zhang, Dan Liu","doi":"10.1109/GRC.2006.1635770","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635770","url":null,"abstract":"Measuring structural similarities is attracting more and more attention from researchers. In this paper, we define structural information content (SIC) for measuring the structural information of a structure, and introduce topological match degree to measure to what extent a subtree is matched. By recursively computing SICs and thus computing topological match degrees, we evaluate the structural information similarities of data trees to pattern tree. In the paper, we present two algorithms for recursively calculating SICs with computation complexity of O(M), and use examples to instantiate the feasibility of the proposed method.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133568465","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}

{"title":"Finding periodicity in pseudo periodic time series and forecasting","authors":"Fei Chen, J. Yuan, Fusheng Yu","doi":"10.1109/GRC.2006.1635858","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635858","url":null,"abstract":"In this paper, pseudo periodic time series are studied. A novel fuzzy granulation based approach is proposed for that. Periodicity discovery and forecast on pseudo periodic time series are concentrated on. Two definitions of periodicity, λ-Pseudo periodicity and generalized λ-Pseudo periodicity are given, and two corresponding algorithms for finding these two kinds of periodicity are designed. These studies are carried on by employing a similarity measure defined on granular value level. Furthermore, we study the forecasting about the development of pseudo periodic time series according to the proposed algorithms. Experiments are given to demonstrate the algorithms. The experimental results show the efficiency of the algorithms, and verify the rationality of the novel fuzzy granulation based approach for studying pseudo periodic time series.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214184","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}

{"title":"An indexation and discovery architecture for semantic web services and its application in bioinformatics","authors":"Liyang Yu, Rajshekhar Sunderraman, Haibin Wang","doi":"10.1109/GRC.2006.1635908","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635908","url":null,"abstract":"Recently much research effort has been devoted to the discovery of relevant Web services. It is also widely recognized that adding semantics to Web service description is the solution to this challenge. Web services with explicit semantic annotation are called Semantic Web Services (SWS). In this paper, we propose an indexation and discovery architecture for semantic Web services, together with an application example in the area of bioinformatics. In our approach, a SWS repository is created and maintained by crawling both the ontology-oriented UDDI registries and the Web sites that hosting SWS. When presented with a service request, the proposed system will invoke the matching algorithm and a candidate set will be returned with different degree of matching being considered. We believe this approach can add more flexibility to the current industry standards by offering more choices to both the service requesters and publishers. Also, the framework in this approach is extensible: different matching algorithms can be easily added, and necessary QoS models can be built on top of the matching algorithms.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131333678","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}

{"title":"Research of the model about the application of granular computing in data fusion system","authors":"Juan Jiang, H. Ding, T. Peng","doi":"10.1109/GRC.2006.1635899","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635899","url":null,"abstract":"Data fusion is one of the most important topics in computer science nowadays. There are 3 levels in data fusion procedure: original level, attribute level, and decision level. Many different technologies have been used in different levels or even the same level. In this paper, it was mainly discussed that the application of GrC (granular computing) used in the attribute level of data fusion system, especially the preprocess of data which were collected from various data sources.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117126553","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}

{"title":"Denotational semantics of dynamic fuzzy logic programming language","authors":"Xiaofang Zhao, Fanzhang Li","doi":"10.1109/GRC.2006.1635827","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635827","url":null,"abstract":"In reference (1), we have given the operational semantics model of dynamic fuzzy logic (DFL) programming language which has an excellent leading meaning to realizers. However, it is hard to see whether the language is well defined. That led us to pay attention to the denotational semantics because it is suitable for testing the validity of the implement of a language. In this paper we research the denotationl semantics of dynamic fuzzy logic programming language, which includes modifying the classical lambda calculus to introduce the character of dynamic fuzzy, the abstract syntax, the descriptions of semantic objects and the handling functions of semantics.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550341","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}

{"title":"Discriminant analysis using nonnegative matrix factorization for nonparametric multiclass classification","authors":"Hyunsoo Kim, Haesun Park","doi":"10.1109/GRC.2006.1635780","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635780","url":null,"abstract":"Linear discriminant analysis (LDA) has been ap- plied to many pattern recognition problems. However, a lot of practical problems require nonnegativity constraints. For exam- ple, pixels in digital images, term frequencies in text mining, and chemical concentrations in bioinformatics should be nonnegative. In this paper, we propose discriminant analysis using nonnegative matrix factorization (DA/NMF), which is a multiclass classifier that generates nonnegative basis vectors. It does not require any parameter optimization and it is intrinsically appropriate for multiclass classifications. It also provides us with the reliability of classification. DA/NMF can be considered as a novel nonnegative dimension reduction algorithm for supervised machine learning problems since it generates nonnegative low-rank representations as well as nonnegative basis vectors. In addition, it can be thought of as nonnegative LDA or the supervised version of NMF.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117205665","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}

{"title":"Graduation and granulation are keys to computation with information described in natural language","authors":"L. Zadeh","doi":"10.1109/GRC.2006.1635751","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635751","url":null,"abstract":"Graduation and granulation play essential roles in human cognition. Both are concomitants of the bounded ability of human sensory organs, and ultimately the brain, to resolve detail and store information. Graduation relates to unsharpness of boundaries or, equivalently, fuzziness. Granulation involves clumping, with a granule being a clump of attribute values drawn together by indistinguishability, similarity, proximity or functionality. Graduation and granulation underlie the concept of a linguistic variable—a concept which plays a pivotal role in fuzzy logic and its applications. What is the connection between graduation, granulation and natural languages? Basically, a natural language is a system for describing perceptions. Perceptions are intrinsically imprecise, reflecting—as do graduation and granulation—the bounded ability of human sensory organs, and ultimately the brain, to resolve detail and store information. Imprecision of perceptions is passed on to natural language. Seen in this perspective, semantic imprecision of natural language is closely linked to graduation and granulation. Imprecision of natural language is a major obstacle to application of conventional methods of computation to computation with information described in natural language. What is computation with information described in natural language? Here are simple examples. I am planning to drive from Berkeley to Santa Barbara, with stopover for lunch in Monterey. It is about 10 am. It will probably take me about two hours to get to Monterey and about an hour to have lunch. From Monterey, it will probably take me about five hours to get to Santa Barbara. What is the probability that I will arrive in Santa Barbara before about six pm? Another simple example: A box contains about twenty balls of various sizes. Most are large. What is the number of small balls? What is the probability that a ball drawn at random is neither small nor large? Another example: A function, f, from reals to reals is described as: If X is small then Y is small; if X is medium then Y is large; if X is large then Y is small. What is the maximum of f? Another example: Usually the temperature is not very low, and usually the temperature is not very high. What is the average temperature? Another example: Usually most United Airlines flights from San Francisco leave on time. What is the probability that my flight will be delayed? Computation with information described in natural language, or NL-computation for short, is a problem of intrinsic importance because much of human knowledge is described in natural","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128439578","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}

{"title":"The case for collaborative distributed wireless intrusion detection systems","authors":"R. Beyah, C. Corbett, J. Copeland","doi":"10.1109/GRC.2006.1635917","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635917","url":null,"abstract":"Since their inception, wireless local area networks (WLANs) have made significant progress in terms of security. They initially suffered from weak authentication, weak encryption, weak message integrity, etc. These weaknesses prompted the formation of the 802.11i standard. The 802.11i standard is a very robust standard that fixes the known problems of its predecessor. This standard also represents a significant development in security; however, it does little to protect authorized users from other authorized users. In this paper, we discuss the evolution of security threats and we make the case for the need for collaborative distributed wireless intrusion detection systems. Further, we introduce the hotspot worm and show, using infectious epidemic models, a worst-case attack that can easily compromise a million users without using the Internet and without being detected.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131082676","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}

{"title":"CM-test: An Innovative Divergence Measurement and Its Application in Diabetes Gene Expression Data Analysis","authors":"L. Liang, Shiyong Lu, Yi Lu, P. Dhawan, D. Kumar","doi":"10.1109/GRC.2006.1635794","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635794","url":null,"abstract":"One important problem in data analysis is to effec- tively measure the divergence of two sets of values of a feature, each from a group of samples with a particular condition. Such a measurement is the foundation for identifying critical features that contribute to the difference between the two conditions. The two traditional methods t-test and Wilcoxon rank sum test measure this divergence indirectly, using the difference of the means of the two groups and the sum of the ranks from one of the groups, respectively. In this paper, we propose an innovative approach based on fuzzy set theory, the Cluster Misclassification test (CM-test), to quantify the divergence directly and robustly. To validate our approach, we conducted experiments on both synthetic and real diabetes gene expression datasets. On the synthetic datasets, we observed that CM-test effectively quantifies the divergence of two sets. On the real diabetes dataset, we observed that in the top ten genes identified by CM-test, eight of them have been confirmed to be associated with diabetes in the literature. We suggest the remaining two genes, M95610 and M88461, as two potential diabetic genes for further biological investigation. Therefore, we recommend that CM-test be another effective method for measuring the divergence of two sets, complementing t-test and Wilcoxon rank sum test in practice.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130792318","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}

{"title":"Application of SVM in web page categorization","authors":"Weimin Xue, Weitong Huang, Yuchang Lu","doi":"10.1109/GRC.2006.1635842","DOIUrl":"https://doi.org/10.1109/GRC.2006.1635842","url":null,"abstract":"Web page classification is an important research direction for web mining. This paper gives some methods for representation of web page, studies on several aspects of support vector machine (SVM) for structural risk minimization concepts of statistical learning theory. The web page classifier and algorithm based on SVM is proposed. Cross validation method is used to select parameters of SVM classifier. The experimental results show that SVM provides an effective method for web page categorization and has promising application in web mining.. . Index Terms—web page categorization, support vector machine, Web Page representation; Kernel function; Web Ming","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132065554","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}