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International Conference on Digital Information Management (ICDIM)

作者： Mikalai Krapivin Maurizio Marchese Andrei Yadrantsau Yanchun Liang Department of Information Engineering and Computer Science University of Trento Italy Department of Computer Science Belarusian State University Minsk Belarus College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University China

The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement of userspsila navigation in the digital content. In this paper, we propose a combined use of machine learning techniques (i.e. Support Vector Machines) and Natural Language Processing techniques (i.e. Stanford NLP parser) to tackle the problem of unsupervised key-phrases extraction from scientific papers. The proposed method strongly depends on the robust structural properties of a scientific paper as well as on the lexical knowledge that we are able to mine from its text. For the experimental assessment we have use a subset of ACM papers in the computer science domain containing 400 documents. Preliminary evaluation of the approach shows promising result that improves - on the same data-set - on state-of-the-art Bayesian learning system KEA from a minimum 27% to a maximum 77% depending on KEA parameters tuning and specific evaluation set. Our assessment is performed by comparison with key-phrases assigned by human experts in the specific domain and freely available through ACM portal.

关键词： Data mining Software libraries Navigation Machine learning Support vector machines Support vector machine classification Natural language processing Robustness computer science Bayesian methods

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Social network analysis of the vulnerabilities of interdependent critical infrastructures

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International Journal of Critical Infrastructures 2008年第3期4卷 256-273页

作者： Chai, Choon-Lee Liu, X. Zhang, W.J. Deters, Ralph Liu, D. Dyachuk, Dmytro Tu, Y.L. Baber, Zaheer Department of Sociology University of Saskatchewan #1019-9 Campus Drive Saskatoon SK S7N 5A5 Canada Department of Mechanical Engineering University of Saskatchewan 57 Campus Dr. Saskatoon SK S7N 5A9 Canada Department of Computer Science University of Saskatchewan 176 Thorvaldson Building 110 Science Place Saskatoon SK S7N 5C9 Canada Department of Mechanical Engineering and Manufacturing Engineering University of Calgary 2500 University Drive NW Calgary AB T2N 1N4 Canada Department of Sociology University of Toronto 725 Spadina Avanue Toronto ON M5S 2J4 Canada Department of Sociology University of Saskatchewan Canada Department of Mechanical and Manufacturing Engineering University of Calgary Canada Department of Mechanical Engineering University of Saskatchewan Canada International Journal of CAD Computer Science Department University of Saskatchewan SME Department of Sociology University of Toronto Knowledge Media Design Institute Centre of Culture Communication and Information Technology

Interdependency among critical infrastructures contributes to vulnerabilities of those infrastructures. In this paper, the vulnerabilities of critical infrastructures are identified and analysed using social network analysis. In the analysis of network centrality, the importance of each critical infrastructure, in terms of its contribution to infrastructure interdependency, is ranked. The findings show that electricity and telecommunication are the two most important critical infrastructures that contribute to infrastructure interdependency, which further render the infrastructure network vulnerable to cascading damage. An example system is given to illustrate the ideas and results presented in this paper. Copyright © 2008 Inderscience Enterprises Ltd.

关键词： computer networks

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SODA-A Distributed Data Management Framework for the Internet of Services

SODA-A Distributed Data Management Framework for the Interne...

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第七届网格与协同计算国际会议(Seventh International Conference on Grid and Cooperative Computing GCC 2008)

作者： Peter Paul Beran Gernot Habel Erich Schikuta University of Vienna Faculty of Computer Science Department of Knowledge and Business Engineering Rathausstr.19/9 A-1010 Vienna Austria

ISBN: (纸本)9781424432806;9780769534497

Soda (Service Oriented Database Architecture) is a proof-of-concept prototype middleware implementation for data intensive applications, where data of relevance is stored at multiple locations over the Internet. Because of its modularity the used Web Services can be plugged together very easily, almost in a LEGOTMalike manner. In fact these services provide the business logic for distributed query execution, specifically supporting autonomous databases in heterogeneous environments. Operations used in this framework – like selection, projection, join, product or sort – can be orchestrated (used, added and removed) dynamically. The architecture is based on the WSRF standard and thus supports stateful Web Services. For reasons of portability it is implemented in Java and uses the WSRFcompatible Apache Muse library.

关键词： Internet computing Web services SOA/SOI Parallel and distributed database operations Query processing Web Service query analysis Internets Legal Services Distributed Data Management Internet services Portability Data management Frameworks

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SocialWeb Communities Executive Summary of the Dagstuhl Seminar

SocialWeb Communities Executive Summary of the Dagstuhl Semi...

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Social Web Communities 2008

作者： Alani, Harith Staab, Steffen Stumme, Gerd Address Harith Research Group ISWeb - Information Systems and Semantic Web University of Koblenz-Landau Univ.str. 1 Koblenz56016 Germany Knowledge & Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 Kassel34121 Germany

Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software. © 2008 Dagstuhl Seminar Proceedings. All rights reserved.

关键词： Natural language processing systems

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A room modeling method for 3D video

A room modeling method for 3D video

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2008 International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA 2008

作者： Isshiki, Aya Sakamoto, Ryuuki Kitahara, Itaru Kogure, Kiyoshi Joe, Kazuki Information and Computer Sciences Department Nara Women's University Nara 630-8506 Japan Department of Computer and Communication Sciences Wakayama University Sakaedani 930 Wakayama Wakayama 640-8510 Japan Department of Intelligent Interaction Technologies Graduate School of Systems and Information Engineering University of Tsukuba Tennoudai 1-1-1 Tsukuba Ibaraki 305-8573 Japan ATR Knowledge Science Laboratories Hikaridai 2-2-2 Keihanna Science City Kyoto 619-0288 Japan

ISBN: (纸本)1601320841

This paper proposes a system to reconstruct the 3D shape model of background regions for generating 3D video easily. As the progress of computer vision technologies continues, many 3D video systems have been developed that tend to focus on automatic 3D reconstruction to capture target (foreground) objects. On the other hand, the 3D shapes of background regions such as walls and floors are generally made manually, for example, using 3D modeling software such as CAD. However, the operation is not easy for novices. Our system provides an easy background modeling method for such users. User operations include segmenting multiple background images into several boxes by indi cating their vertices and giving the correspondence of the boxes between multiple images. As a result, the 3D coordinates of the vertices are calculated using a stereo vision algorithm.

关键词： Stereo vision

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An independence of causal interactions model for opposing inuences

An independence of causal interactions model for opposing in...

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4th European Workshop on Probabilistic Graphical Models, PGM 2008

作者： Maaskant, Paul P. Druzdzel, Marek J. Department of Media and Knowledge Engineering Delft University of Technology 2628 CD Delft Netherlands Faculty of Computer Science Bia Lystok Technical University Wiejska 45A 15-351 Bia lystok Poland Decision Systems Laboratory School of Information Sciences University of Pittsburgh Pittsburgh PA 15260 United States

We introduce the DeMorgan gate, an Independence of Causal Interactions (ICI) model that is capable of modeling opposing inuences, i.e., a mixture of positive and negative inuences of parents on a child. The model is a noisy version of a conjunctive normal form of Boolean functions and is an extension and a combination of the popular Noisy OR and Noisy-AND models, preserving their intuitive semantics. We report the results of a simple experiment testing the usefulness of the proposed model for elicitation of conditional probability distributions.

关键词： Semantics

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Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval

Automatic Recommendations for E-Learning Personalization Bas...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Mohamed Koutheaïr Khribi Mohamed Jemni Olfa Nasraoui Technologies of Information and Communication Lab University of Tunis Tunis Bab Mnara TUNISIA Knowledge Discovery & Web Mining Lab Department of Computer Engineering & Computer Science Speed School of Engineering University of Louisville Louisville KY USA

The World Wide Web (WWW) is becoming one of the most preferred and widespread mediums of learning. Unfortunately, most of the current Web-based learning systems are still delivering the same educational resources in the same way to learners with different profiles. A number of past efforts have dealt with e-learning personalization, generally, relying on explicit information. In this paper, we aim to compute on-line automatic recommendations to an active learner based on his/her recent navigation history, as well as exploiting similarities and dissimilarities among user preferences and among the contents of the learning resources. First we start by mining learner profiles using Web usage mining techniques and content-based profiles using information retrieval techniques. Then, we use these profiles to compute relevant links to recommend for an active learner by applying a number of different recommendation strategies.

关键词： Electronic learning Information retrieval Navigation Information filtering Information filters Uniform resource locators Data mining knowledge engineering History Collaboration

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Detecting DNA-binding Domain From Sequence and Secondary Structure Information Using Kernel-based Technique

Detecting DNA-binding Domain From Sequence and Secondary Str...

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2008 3rd International Conference on Intelligent System and knowledge engineering(第三届智能系统与知识工程国际会议)(ISKE 2008)

作者： Wang Fei Chen Lusheng Shanghai key laboratory of Intelligent Information Processing Fudan UniversityPRC Department of Computer Science and EngineeringFudan UniversityPRC Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin Universi

DNA-binding proteins play an important role invarious intra-and extra-cellular *** key in theprotein is DNA-binding region also called DNA-bindingdomain(DBD).However,it is hard to search the DBDsby means of homology search or hidden Markov modelsbecause of a wide variety of the *** this work,we develop a kernel-based machine learning method bycombination of multiple "l-vs-l" binary classifiers forDNA binding domain *** result shows that93.73％ accuracy is achieved for multicategory classifierand no less than 90％ accuracy for each binary *** comparison,our classifier performs better than othermachine learning methods.

关键词： Support vector machines Sequences Hidden Markov models Learning systems DNA knowledge engineering Partial response channels Protein engineering Support vector machine classification Intelligent systems

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Translating Query for Deep Web Using Ontology

Translating Query for Deep Web Using Ontology

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International Conference on computer science and Software engineering

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

ISBN: (纸本)9781424439027

The e-commerce information on the surface Web is supported by the Deep Web, which can not be accessed directly by the search engines or the Web crawlers. The only way to access the backend database is through query interface. Extracting valid attributes from the query forms and automatic translating the source query into a target query is a solvable way for addressing the current limitations in accessing Deep Web data sources. To generate a valid query, we have to reconcile the key attributes and their semantic relation. We present our framework to solve the problem. To enrich the set of attributes contained in the semantic form, we use the WordNet as kinds of ontology technique and we try to find the semantic relation of the attributes in the same query from and different forms. Extensive experiments over real-word domains show the utility of our query translation framework.

关键词： Ontologies Databases computer science Educational institutions Search engines Data mining Laboratories knowledge engineering computer science education Crawlers

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Describing low-level image features using the COMM ontology

Describing low-level image features using the COMM ontology

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IEEE International Conference on Image Processing

作者： Miroslav Vacura Vojtech Svatek Carsten Saathoff Thomas Franz Raphael Troncy Prague Department of Information and Knowledge Engineering University of Economics Praque Czech Republic Institute for Computer Science University of Koblenz-Landau ISWeb Group Koblenz Germany CWI Amsterdam Netherlands

We present an innovative approach for storing and processing extracted low-level image features based on current semantic Web technologies. We propose to use the COMM multimedia ontology as a "semantic" alternative to the MPEG-7 standard, which is at the same time largely compliant with it. We describe how COMM can be used directly or through its associated Java API.

关键词： Ontologies MPEG 7 Standard Resource description framework Data mining Semantic Web XML OWL Image segmentation Feature extraction Java

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