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computer science and Information engineering, CSIE, WRI World Congress on FLAGGED

作者： Hao Liang Fei Ren Wanli Zuo Fengling He Junhua Wang College of Computer Science and Technology Jilin University Changchun China Department of Information Changchun Taxation College Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun China

There is myriad high quality information in the Deep Web and the feasible method to access the Deep Web is through the query interface of the Deep Web. Itpsilas necessary to extract abundant attributes and semantic relation description from the query interface. Automatic extracting attributes from the query interface and automatically translating a query is a solvable way for addressing the current limitations in accessing Deep Web data sources. We design a framework to automatically extract the attributes and instances from the query interface using the WordNet as a kind of ontology technique to enrich the semantic description of the attributes. Each attribute is extended into a candidate attribute set in the form of a hierarchy tree. At the same time, the hierarchy tree generated by ontology describes the semantic relation of the attributes in the same query interface. We carry out our experiments in the real-world domain. The results of the experiments showed the validation of query translation framework.

关键词： Data mining Ontologies computer science Educational institutions Databases Programming profession HTML Laboratories computer interfaces knowledge engineering

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The Ontology Based Semantic Evaluating Method in LAV

The Ontology Based Semantic Evaluating Method in LAV

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Pacific-Asia Conference on Circuits, Communications and Systems, PACCS

作者： Fei Ren Hao Liang Liang Hu Wanli Zuo College of Computer Science and Technology Jilin University Changchun China Department of Information Changchun Taxation College Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China

The Web has been dramatically deepened by the deep Web, which the traditional information fusion system shows disability to integrate. The myriad information hidden behind the deep Web attracts the considerable attention from the researchers. The key element in a deep Web information fusion system is the data source modeling problem, which determine the whole technical method 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 low generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of evaluating the semantic relationships between the attributes in the query interfaces by utilizing WordNet, a typical ontology technique, is presented in this paper. The semantic relationships between semantic related attributes are evaluated by the semantic calculating method of WordNet. The meaningless attributes is instantiated by instance information embedded in the interfaces in order to attach correlated semantic information. The experiment is carried out in the real life domains, and the result shows the efficiency of ontology based semantic evaluating method in LAV.

关键词： Ontologies Databases Educational institutions computer science Educational technology Search engines Circuits Laboratories knowledge engineering computer science education

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Learning a nonlinear color distance metric for the identification of skin immunohistochemical staining

Learning a nonlinear color distance metric for the identific...

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2009 22nd IEEE International Symposium on computer-Based Medical Systems, CBMS 2009

作者： Sobieranski, Antonio Carlos Neto, Sylvio Luiz Mantelli Coser, Leandro Comunello, Eros Von Wangenheim, Aldo Cargnin-Ferreira, Eduardo Di Giunta, Gabriella LAPIX Laboratory of Image Processing and Computer Graphics UFSC Federal University of Santa Catarina Brazil CPTEC Center for Weather Forecasts and Environment Studies INPE - Brazilian Institute for Space Research Brazil EGC Knowledge Engineering Department UFSC - Federal University of Santa Catarina Brazil MCA Graduate Program in Applied Computer Science UNIVALI - Itajai Valley University Brazil Laboratory of Histological Markers Department of Biology Embriology and Genetics UFSC - Federal University of Santa Catarina Brazil Pathology Service UFSC - Federal University of Santa Catarina Brazil

ISBN: (纸本)9781424448784

This paper presents a semiautomatic method for the identification of immunohistochemical (IHC) staining in digitized samples. The user trains the system by selecting on a sample image some typical positive stained regions that will be used as a reference for the construction of a distance metric. In this learning process, the global optimum is obtained by induction employing higher polynomial terms of the Mahalanobis distance, extracting nonlinear features of the IHC pattern distributions. The results of the proposed method showed a high correlation to a pathologist's manual analysis, which was used as a golden standard, presenting a more robust discrimination between stained and non-stained areas with little bias. © 2009 IEEE.

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ADAM: Web Anomaly Detection Assistant Based on Feature Matrix

ADAM: Web Anomaly Detection Assistant Based on Feature Matri...

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International Conference on Quality Software

作者： Sungdeok Cha Junsup Lee Sangrok Kim Sanghyun Cho Department of Computer Science and Engineering Korea University Seoul South Korea Knowledge e-learning research team Electronics and Telecommunications Research Institute Daejeon South Korea Financial Supervisory Service Seoul South Korea NHN Corporation Gyeonggi South Korea

ISBN: (纸本)9781424459124

Importance of web security cannot be overemphasized in the era of web-based economy. Although anomaly detection has long been considered a promising alternative to signature-based misuse detection technique, most studies to date used either small scale or artificially generated attack data. In this paper, based on security analysis applied on anonymous *** log of about 250 GB, we propose Anomaly Feature Matrix (AFM) as an effective framework to characterize anomalies. Feature selection of AFM is based on the characteristics of well-known (e.g., DDoS) attacks as well as patterns of anomalous logs found in the Microsoft data. Independent security analysis performed on the same data by Microsoft security engineers concluded that 1) We did not miss any major attacks; and 2) AFM is a general enough framework to characterize likely web attacks. In order to assist AFM-based anomaly analysis in large organizations, we implemented an interactive and visual analysis tool named ADAM (Anomaly Detection Assistant based on feature Matrix). Integrated with mapping software such as Virtual Earth, ADAM enables efficient and focused security analysis on web logs.

关键词： Data security Performance analysis Web server Visualization Data engineering Earth Privacy Feedback Open source software Network address translation

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2009年 5476 LNAI卷 v-vi页

作者： Theeramunkong, Thanaruk Kijsirikul, Boonserm Cercone, Nick Ho, Tu-Bao Thammasat University Sirindhorn International Institute of Technology 131 Moo 5 Tiwanont Road Bangkadi Muang Pathumthani 12000 Thailand Chulalongkorn University Faculty of Engineering Department of Computer Engineering Bangkok 10330 Thailand York University Faculty of Science and Engineering 355 Lumbers Building 4700 Keele Street Toronto ON M3J 1P3 Canada Japan Advanced Institute of Science and Technology School of Knowledge Science 1-1 Asahidai Nomi Ishikawa 923-1292 Japan

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Exploring cost-sensitive learning in domain based protein-protein interaction prediction 6

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6th International Symposium of Neural Networks, ISNN 2009

作者： Guo, Weizhao Hu, Yong Liu, Mei Yin, Jian Xie, Kang Yang, Xiaobo School of Information Science and Technology Sun Yat-sen University Guangzhou510275 China Business Intelligence and Knowledge Discovery Guangdong University of Foreign Studies Sun Yat-sen University Guangzhou510275 China Bioinformatics and Computational Life-Sciences Laboratory ITTC Department of Electrical Engineering and Computer Science The University of Kansas 1520 West 15th Street LawrenceKS66045 United States School of Business Sun Yat-sen University Guangzhou510275 China The 2nd Affiliated Hospital Guangzhou University of TCM Guangzhou510120 China

ISBN: (纸本)9783642012150

Protein interactions are of great biological interest because they orchestrate nearly all cellular processes and can further our understandings in biological processes and diseases. Protein interaction data like many real world datasets are imbalanced in nature. Most protein pairs belong to the non-interaction class and few belong to the interaction class. Most existing protein interaction prediction methods assume equal distribution of the positive and negative interaction data. In this study, we first analyze effects of various portions of negative samples on the performance of domain-based protein interaction prediction methods using Artificial Neural Network (ANN), Bayesian Network (BN), and SVM. Then we introduce cost-sensitive learning to address the class imbalance problem. Experimental results demonstrated that the addition of cost-sensitive learning to each classifier: ANN, BN, and SVM, indeed yields an increase in accuracy. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Bayesian networks

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Case-based reasoning and fuzzy logic in fault diagnosis

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WSEAS Transactions on computers 2009年第8期8卷 1408-1417页

作者： Marques, Viriato Farinha, J. Torres Brito, António GECAD-Knowledge Engineering and Decision Support Research Centre ISEP-Engineering Institute-Oporto Polytechnic Institute Rua Dr. António Bernardino de-Almeida 431 4200-072 Porto Portugal Computer Science Department ISEC-Engineering Institute-Coimbra Polytechnic Institute Quinta da Nora 3030-199 Coimbra Portugal Mechanical Engineering Department ISEC-Engineering Institute-Coimbra Polytechnic Institute Quinta da Nora 3030-199 Coimbra Portugal Mechanical Engineering Department FEUP- Engineering Faculty of Oporto University R.Dr.Roberto Frias 4200-065 Porto Portugal

This paper is divided into four parts: the first one introduces SADEX, a fuzzy Case Based Reasoning (CBR) System for fault diagnosis. The second focus on its observation relevance factors and shows how the results are in complete agreement with the relevance concept introduced by Robertson and Spark-Jones in their well known and proved technique for document retrieval. The third describes how equipment composition information can be used to generalize and adapt case solutions to new and unknown occurrences;this generalization is based on a taxonomic similarity between functionally autonomous modules (FAMs). Finally the MKM-Maintenance knowledge Manager system is introduced.

关键词： Case based reasoning

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Canonical Huffman code based full-text index

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Progress in Natural science:Materials International 2008年第3期18卷 325-330页

作者： Yi Zhang a,b, Zhili Pei a, Jinhui Yanga, Yanchun Liang a, a College of computer science and Technology, Jilin University, Key Laboratory of Symbol Computation and knowledge engineering of the Ministry of Education, Changchun 130012, China b department of computer science, Jilin Technology and Business College, Changchun 130062, China College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Department of Computer Science Jilin Technology and Business College Changchun 130062 China

Full-text indices are data structures that can be used to find any substring of a given string. Many full-text indices require space larger than the original string. In this paper, we introduce the canonical Huffman code to the wavelet tree of a string T[1. . .n]. Compared with Huffman code based wavelet tree, the memory space used to represent the shape of wavelet tree is not needed. In case of large alphabet, this part of memory is not negligible. The operations of wavelet tree are also simpler and more efficient due to the canonical Huffman code. Based on the resulting structure, the multi-key rank and select functions can be performed using at most nH0 + jRj(lglgn + lgn lgjRj)+O(nH0) bits and in O(H0) time for average cases, where H0 is the zeroth order empirical entropy of T. In the end, we present an efficient construction algorithm for this index, which is on-line and linear.

关键词： Full-text index Su?x automaton Canonical Hu?man code

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S-SimRank: Combining Content and Link Information to Cluster Papers Effectively and Efficiently

S-SimRank: Combining Content and Link Information to Cluster...

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4th International Conference on Advanced Data Mining and Applications

作者： Cai, Yuanzhe Li, Pei Liu, Hongyan He, Jun Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China Department of Computer Science Renmin University of China China Department of Management Science and Engineering Tsinghua University China

ISBN: (纸本)9783540881919

Both Content analysis and link, analysis have its advantages in measuring relationships among documents. In this paper. we propose a new method to combine these two methods to compute the similarity of research papers so that we can do clustering of these papers more accurately. In order to improve the efficiency of similarity calculation, we develop a strategy to deal with the relationship graph separately, without affecting the accuracy. We also design an approach to assign different weights to different links to the papers, which can enhance the accuracy of similarity calculation. The experimental results conducted oil ACM Data Set show that our new algorithm. S-SimRank, outperforms other algorithms.

关键词： Calculations

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SimCon: A tool for modeling context sources for rapid evaluation of pervasive applications using virtual reality 5

SimCon: A tool for modeling context sources for rapid evalua...

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5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2008

作者： McGlinn, Kris O'Neill, Eleanor Lewis, David Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin Dublin 2 Ireland

Here we present the SimCon tool to enable evaluators of pervasive applications to rapidly place and configure context sources within a Virtual Reality Environment to conduct repeatable evaluations early in the develop... 详细信息

ISBN: (纸本)9789639799219

关键词： Ubiquitous computing

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