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Advances in scalable web information integration and service [[electronic resource] ] : proceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 / / editors, Yoshifumi Masunaga ... [et al.]
| Advances in scalable web information integration and service [[electronic resource] ] : proceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 / / editors, Yoshifumi Masunaga ... [et al.] |
| Pubbl/distr/stampa | New Jersey, : World Scientific, c2007 |
| Descrizione fisica | 1 online resource (128 p.) |
| Disciplina | 006.7 |
| Altri autori (Persone) | MasunagaY <1941-> (Yoshifumi) |
| Soggetto topico |
Web services
Semantic Web Information retrieval Data mining Internet searching |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-91906-3
9786611919061 981-277-024-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Table of Contents; Preface; Invited Session; Using Semantics in XML Data Management Tok Wang Ling and Gillian Dobbie; 1. Introduction; 2. Related Work; 3. The ORA-SS Data Model; 4. Using Semantics in Query Processing; 5. Content Search in XML; 6. Keyword Search with Semantics in XML; 7. Conclusion; References; Processing Web Aggregate Queries by Analyzing Search Engine Indices Satoshi Oyama, Taro Tezuka, Hiroaki Ohshima and Katsumi Tanaka; 1. Introduction; 2. A Two-phase Method for Processing Web Aggregate Queries; 2.1. Probe phase; 2.2. Validation phase
3. Composing Probe and Validation Phases3.1. Access to search engine indices; 3.2. Search with document structures/ linguistic patterns; 3.3. Aggregation; 3.4. Filtering; 4. Web Aggregate Queries; 4.1. Finding typical topics; 4.2. Finding siblings/rivals; 4.3. Finding Landmarks; 5. Conclusion; Acknowledgments; References; Process Mining for Composite Web Services Aiqiang Gao, Dongqing Yang, Shiwei Tang and Yan Fu; 1. Introduction; 2. A Process Model for Composite Web Services; 2.1. Describing Web Services; 2.2. Workflow Graphs; 2.3. A Graph-based Model for Composite Web Services 3. Supporting Data Structures3.1. Execution Logs; 3.2. Supporting Data Structure; 4. Process Mining Method; 4.1. Main Algorithm; 4.2. Sub-Algorithms Details; 5. Illustration Examples; 6. Related Works; 7. Conclusion; References; Session 1: Semantic Web and Deep Web; Web Resource Categorization for Semantic Web Search M. Pei, K. Nakayama, T. Hara and S. Nishio; 1. Introduction; 2. Categorization Algorithm; 2.1. Approach; 2.2. Process 1: Categorize Offspring; 2.3. Process 2: Extend Category Based on Characteristic Class Name; 2.4. Process 3: Detect Potential Relation from Dictionary 2.5. Process 4: Detect Relation by Property Pattern Analysis2.6. Flow of Whole Categorization; 3. Experiment for CSWS; 3.1. Data Sources and Evaluations; 3.2. Evaluation Results; 3.3. Comparison with Corese; 4. Conclusions; References; An Effective TOP-K Data Sources Ranking Approach on Deep Web Meifang Li, Guangqi Wang, Derong Shen, Tiezheng Nie, HongKai Zhu and Ge Yu; 1. Introduction; 2. AFP-growth Algorithm; 3. Relevant Attributes Matrix (RAM); 4. Dominance and Relevance based Top-k Style Ranking Algorithm (DR-TRA); 5. Experimental Evaluation; 5.1. Datasets and Setup 5.2. Performance Comparisons6. Related Work; 7. Conclusions; References; Session 2: Web Service; Automated Web Service Discovery Lev Shulman, Elias Ioup, John Sample, Kevin Shaw and Mahdi Abdelguerfi; 1. Introduction; 2. Background; 2.1. Web Services; 2.2. OGC Geospatial Web Services; 2.3. Previous Work; 3. Web Service Discovery; 4. Validation and Portal Integration; 5. Results; 6. Conclusion; Acknowledgments; References; Visual Media Data Retrieval Based on Web Service Matchmaking Seong-Woo Lee, Chulbum Ahn, Bowon Suh, O-Byoung Kwon and Yunmook Nah; 1. Introduction 2. Overview of Visual Media Service Architecture |
| Record Nr. | UNINA-9910451320503321 |
| New Jersey, : World Scientific, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in scalable web information integration and service [[electronic resource] ] : proceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 / / editors, Yoshifumi Masunaga ... [et al.]
| Advances in scalable web information integration and service [[electronic resource] ] : proceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 / / editors, Yoshifumi Masunaga ... [et al.] |
| Pubbl/distr/stampa | New Jersey, : World Scientific, c2007 |
| Descrizione fisica | 1 online resource (128 p.) |
| Disciplina | 006.7 |
| Altri autori (Persone) | MasunagaY <1941-> (Yoshifumi) |
| Soggetto topico |
Web services
Semantic Web Information retrieval Data mining Internet searching |
| ISBN |
1-281-91906-3
9786611919061 981-277-024-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Table of Contents; Preface; Invited Session; Using Semantics in XML Data Management Tok Wang Ling and Gillian Dobbie; 1. Introduction; 2. Related Work; 3. The ORA-SS Data Model; 4. Using Semantics in Query Processing; 5. Content Search in XML; 6. Keyword Search with Semantics in XML; 7. Conclusion; References; Processing Web Aggregate Queries by Analyzing Search Engine Indices Satoshi Oyama, Taro Tezuka, Hiroaki Ohshima and Katsumi Tanaka; 1. Introduction; 2. A Two-phase Method for Processing Web Aggregate Queries; 2.1. Probe phase; 2.2. Validation phase
3. Composing Probe and Validation Phases3.1. Access to search engine indices; 3.2. Search with document structures/ linguistic patterns; 3.3. Aggregation; 3.4. Filtering; 4. Web Aggregate Queries; 4.1. Finding typical topics; 4.2. Finding siblings/rivals; 4.3. Finding Landmarks; 5. Conclusion; Acknowledgments; References; Process Mining for Composite Web Services Aiqiang Gao, Dongqing Yang, Shiwei Tang and Yan Fu; 1. Introduction; 2. A Process Model for Composite Web Services; 2.1. Describing Web Services; 2.2. Workflow Graphs; 2.3. A Graph-based Model for Composite Web Services 3. Supporting Data Structures3.1. Execution Logs; 3.2. Supporting Data Structure; 4. Process Mining Method; 4.1. Main Algorithm; 4.2. Sub-Algorithms Details; 5. Illustration Examples; 6. Related Works; 7. Conclusion; References; Session 1: Semantic Web and Deep Web; Web Resource Categorization for Semantic Web Search M. Pei, K. Nakayama, T. Hara and S. Nishio; 1. Introduction; 2. Categorization Algorithm; 2.1. Approach; 2.2. Process 1: Categorize Offspring; 2.3. Process 2: Extend Category Based on Characteristic Class Name; 2.4. Process 3: Detect Potential Relation from Dictionary 2.5. Process 4: Detect Relation by Property Pattern Analysis2.6. Flow of Whole Categorization; 3. Experiment for CSWS; 3.1. Data Sources and Evaluations; 3.2. Evaluation Results; 3.3. Comparison with Corese; 4. Conclusions; References; An Effective TOP-K Data Sources Ranking Approach on Deep Web Meifang Li, Guangqi Wang, Derong Shen, Tiezheng Nie, HongKai Zhu and Ge Yu; 1. Introduction; 2. AFP-growth Algorithm; 3. Relevant Attributes Matrix (RAM); 4. Dominance and Relevance based Top-k Style Ranking Algorithm (DR-TRA); 5. Experimental Evaluation; 5.1. Datasets and Setup 5.2. Performance Comparisons6. Related Work; 7. Conclusions; References; Session 2: Web Service; Automated Web Service Discovery Lev Shulman, Elias Ioup, John Sample, Kevin Shaw and Mahdi Abdelguerfi; 1. Introduction; 2. Background; 2.1. Web Services; 2.2. OGC Geospatial Web Services; 2.3. Previous Work; 3. Web Service Discovery; 4. Validation and Portal Integration; 5. Results; 6. Conclusion; Acknowledgments; References; Visual Media Data Retrieval Based on Web Service Matchmaking Seong-Woo Lee, Chulbum Ahn, Bowon Suh, O-Byoung Kwon and Yunmook Nah; 1. Introduction 2. Overview of Visual Media Service Architecture |
| Record Nr. | UNINA-9910777491403321 |
| New Jersey, : World Scientific, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in scalable web information integration and service [[electronic resource] ] : proceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 / / editors, Yoshifumi Masunaga ... [et al.]
| Advances in scalable web information integration and service [[electronic resource] ] : proceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 / / editors, Yoshifumi Masunaga ... [et al.] |
| Pubbl/distr/stampa | New Jersey, : World Scientific, c2007 |
| Descrizione fisica | 1 online resource (128 p.) |
| Disciplina | 006.7 |
| Altri autori (Persone) | MasunagaY <1941-> (Yoshifumi) |
| Soggetto topico |
Web services
Semantic Web Information retrieval Data mining Internet searching |
| ISBN |
1-281-91906-3
9786611919061 981-277-024-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Table of Contents; Preface; Invited Session; Using Semantics in XML Data Management Tok Wang Ling and Gillian Dobbie; 1. Introduction; 2. Related Work; 3. The ORA-SS Data Model; 4. Using Semantics in Query Processing; 5. Content Search in XML; 6. Keyword Search with Semantics in XML; 7. Conclusion; References; Processing Web Aggregate Queries by Analyzing Search Engine Indices Satoshi Oyama, Taro Tezuka, Hiroaki Ohshima and Katsumi Tanaka; 1. Introduction; 2. A Two-phase Method for Processing Web Aggregate Queries; 2.1. Probe phase; 2.2. Validation phase
3. Composing Probe and Validation Phases3.1. Access to search engine indices; 3.2. Search with document structures/ linguistic patterns; 3.3. Aggregation; 3.4. Filtering; 4. Web Aggregate Queries; 4.1. Finding typical topics; 4.2. Finding siblings/rivals; 4.3. Finding Landmarks; 5. Conclusion; Acknowledgments; References; Process Mining for Composite Web Services Aiqiang Gao, Dongqing Yang, Shiwei Tang and Yan Fu; 1. Introduction; 2. A Process Model for Composite Web Services; 2.1. Describing Web Services; 2.2. Workflow Graphs; 2.3. A Graph-based Model for Composite Web Services 3. Supporting Data Structures3.1. Execution Logs; 3.2. Supporting Data Structure; 4. Process Mining Method; 4.1. Main Algorithm; 4.2. Sub-Algorithms Details; 5. Illustration Examples; 6. Related Works; 7. Conclusion; References; Session 1: Semantic Web and Deep Web; Web Resource Categorization for Semantic Web Search M. Pei, K. Nakayama, T. Hara and S. Nishio; 1. Introduction; 2. Categorization Algorithm; 2.1. Approach; 2.2. Process 1: Categorize Offspring; 2.3. Process 2: Extend Category Based on Characteristic Class Name; 2.4. Process 3: Detect Potential Relation from Dictionary 2.5. Process 4: Detect Relation by Property Pattern Analysis2.6. Flow of Whole Categorization; 3. Experiment for CSWS; 3.1. Data Sources and Evaluations; 3.2. Evaluation Results; 3.3. Comparison with Corese; 4. Conclusions; References; An Effective TOP-K Data Sources Ranking Approach on Deep Web Meifang Li, Guangqi Wang, Derong Shen, Tiezheng Nie, HongKai Zhu and Ge Yu; 1. Introduction; 2. AFP-growth Algorithm; 3. Relevant Attributes Matrix (RAM); 4. Dominance and Relevance based Top-k Style Ranking Algorithm (DR-TRA); 5. Experimental Evaluation; 5.1. Datasets and Setup 5.2. Performance Comparisons6. Related Work; 7. Conclusions; References; Session 2: Web Service; Automated Web Service Discovery Lev Shulman, Elias Ioup, John Sample, Kevin Shaw and Mahdi Abdelguerfi; 1. Introduction; 2. Background; 2.1. Web Services; 2.2. OGC Geospatial Web Services; 2.3. Previous Work; 3. Web Service Discovery; 4. Validation and Portal Integration; 5. Results; 6. Conclusion; Acknowledgments; References; Visual Media Data Retrieval Based on Web Service Matchmaking Seong-Woo Lee, Chulbum Ahn, Bowon Suh, O-Byoung Kwon and Yunmook Nah; 1. Introduction 2. Overview of Visual Media Service Architecture |
| Record Nr. | UNINA-9910812174603321 |
| New Jersey, : World Scientific, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Automating open source intelligence : algorithms for OSINT / / edited by Robert Layton, Paul A. Watters
| Automating open source intelligence : algorithms for OSINT / / edited by Robert Layton, Paul A. Watters |
| Pubbl/distr/stampa | Amsterdam : , : Elsevier, , [2016] |
| Descrizione fisica | 1 online resource (212 pages) : illustrations, charts |
| Collana | Syngress advanced topics in information security |
| Soggetto topico |
Open source intelligence
Information technology - Social aspects Business intelligence - Computer network resources Intelligence service - Computer network resources Data mining Internet searching Computational intelligence |
| ISBN | 0-12-802917-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Chapter 1 - The Automating of Open Source Intelligence; The Commercial Angle; Algorithms; References; Chapter 2 - Named Entity Resolution in Social Media; Introduction; Evaluating Semantic Processing Performance; Characterizing Semantic Processing Errors; Meaning Loss in Biblical Proverbs: A Case Study; Models for Improving Semantic Processing Performance; Discussion; References; Chapter 3 - Relative Cyberattack Attribution; Introduction; Basic Attack Structure; Anonymization on the Internet; Weaknesses in Anonymization
Attribution as a ConceptAbsolute Attribution; Relative Attribution; Relative attribution concepts; Inherent versus Learnt Behaviors; Hiding Behavior; Consistency of Behavior; Relative Attribution Techniques; Authorship Analysis; Limitations and Issues; Research Streams; Conclusions; References; Chapter 4 - Enhancing Privacy to Defeat Open Source Intelligence; Introduction; Scenario; Requirements and Threats; Preliminaries; The PIEMCP; Formal Security Analysis with CPN; Attack Scenarios; Verification Results; Removing Trusted ARM; Performance Analysis of FSSO-PIEMC Comparison to Existing ApproachConclusion and future work; References; Chapter 5 - Preventing Data Exfiltration: Corporate Patterns and Practices; What is Happening Around the World?; What is Happening in New Zealand?; Specifying the Problem; Problems Arising by Implementing Censorship; So, what should be done?; Summary; References; Chapter 6 - Gathering Intelligence on High-Risk Advertising and Film Piracy: A Study of the Digital Underground; Introduction; Advertising and risk; The digital millennium copyright act (DMCA); Chilling Effects Database; Google Transparency Report Mainstream advertising and how piracy is fundedHigh-Risk Advertising and their links to piracy websites; High-Risk Advertising: Case Studies in Canada; High-risk advertising: case studies in Australia; High-Risk Advertising: Case studies in New Zealand; Research Challenges; References; Chapter 7 - Graph Creation and Analysis for Linking Actors: Application to Social Data; Introduction; The Social Network Model; A Brief History of Graphs and Social Networks; Conceptual Framework; Graph Creation Techniques; Data Gathering; Defining and Computing Relationships; Disambiguation Techniques Graph Analysis for OSINTStructural Observations; Density of a Graph; Neighborhood, Degree, Average Degree, and Degree Distribution; Paths and Average Path Length; Components; Characterizing Position of Nodes; Betweenness Centrality; Closeness Centrality; Structures and Communities of Nodes; Structural Patterns: Cliques and Cores; Communities; Modularity; Twitter Case Study; The Twitter Dataset; General Graph Metrics; Node Metrics and Profiles' Centrality; Communities; Conclusion; References; Chapter 8 - Ethical Considerations When Using Online Datasets for Research Purposes; Introduction Existing Guidelines |
| Record Nr. | UNINA-9910797822003321 |
| Amsterdam : , : Elsevier, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Automating open source intelligence : algorithms for OSINT / / edited by Robert Layton, Paul A. Watters
| Automating open source intelligence : algorithms for OSINT / / edited by Robert Layton, Paul A. Watters |
| Pubbl/distr/stampa | Amsterdam : , : Elsevier, , [2016] |
| Descrizione fisica | 1 online resource (212 pages) : illustrations, charts |
| Collana | Syngress advanced topics in information security |
| Soggetto topico |
Open source intelligence
Information technology - Social aspects Business intelligence - Computer network resources Intelligence service - Computer network resources Data mining Internet searching Computational intelligence |
| ISBN | 0-12-802917-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Chapter 1 - The Automating of Open Source Intelligence; The Commercial Angle; Algorithms; References; Chapter 2 - Named Entity Resolution in Social Media; Introduction; Evaluating Semantic Processing Performance; Characterizing Semantic Processing Errors; Meaning Loss in Biblical Proverbs: A Case Study; Models for Improving Semantic Processing Performance; Discussion; References; Chapter 3 - Relative Cyberattack Attribution; Introduction; Basic Attack Structure; Anonymization on the Internet; Weaknesses in Anonymization
Attribution as a ConceptAbsolute Attribution; Relative Attribution; Relative attribution concepts; Inherent versus Learnt Behaviors; Hiding Behavior; Consistency of Behavior; Relative Attribution Techniques; Authorship Analysis; Limitations and Issues; Research Streams; Conclusions; References; Chapter 4 - Enhancing Privacy to Defeat Open Source Intelligence; Introduction; Scenario; Requirements and Threats; Preliminaries; The PIEMCP; Formal Security Analysis with CPN; Attack Scenarios; Verification Results; Removing Trusted ARM; Performance Analysis of FSSO-PIEMC Comparison to Existing ApproachConclusion and future work; References; Chapter 5 - Preventing Data Exfiltration: Corporate Patterns and Practices; What is Happening Around the World?; What is Happening in New Zealand?; Specifying the Problem; Problems Arising by Implementing Censorship; So, what should be done?; Summary; References; Chapter 6 - Gathering Intelligence on High-Risk Advertising and Film Piracy: A Study of the Digital Underground; Introduction; Advertising and risk; The digital millennium copyright act (DMCA); Chilling Effects Database; Google Transparency Report Mainstream advertising and how piracy is fundedHigh-Risk Advertising and their links to piracy websites; High-Risk Advertising: Case Studies in Canada; High-risk advertising: case studies in Australia; High-Risk Advertising: Case studies in New Zealand; Research Challenges; References; Chapter 7 - Graph Creation and Analysis for Linking Actors: Application to Social Data; Introduction; The Social Network Model; A Brief History of Graphs and Social Networks; Conceptual Framework; Graph Creation Techniques; Data Gathering; Defining and Computing Relationships; Disambiguation Techniques Graph Analysis for OSINTStructural Observations; Density of a Graph; Neighborhood, Degree, Average Degree, and Degree Distribution; Paths and Average Path Length; Components; Characterizing Position of Nodes; Betweenness Centrality; Closeness Centrality; Structures and Communities of Nodes; Structural Patterns: Cliques and Cores; Communities; Modularity; Twitter Case Study; The Twitter Dataset; General Graph Metrics; Node Metrics and Profiles' Centrality; Communities; Conclusion; References; Chapter 8 - Ethical Considerations When Using Online Datasets for Research Purposes; Introduction Existing Guidelines |
| Record Nr. | UNINA-9910817908603321 |
| Amsterdam : , : Elsevier, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Conducting web-based surveys [[electronic resource] /] / Solomon, David J
| Conducting web-based surveys [[electronic resource] /] / Solomon, David J |
| Autore | Solomon David J |
| Pubbl/distr/stampa | College Park, MD : , : ERIC Clearinghouse on Assessment and Evaluation, , [2001] |
| Collana | ERIC/AE digest series |
| Soggetto topico |
Surveys - Data processing
Social surveys - Response rate Internet searching |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Conducting web based surveys |
| Record Nr. | UNINA-9910692851503321 |
Solomon David J
|
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| College Park, MD : , : ERIC Clearinghouse on Assessment and Evaluation, , [2001] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data management in the semantic web [[electronic resource] /] / Hal Jin, editor
| Data management in the semantic web [[electronic resource] /] / Hal Jin, editor |
| Pubbl/distr/stampa | Hauppauge, N.Y., : Nova Science Publishers, c2012 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina | 025.042/7 |
| Altri autori (Persone) | JinHal |
| Collana | Distributed, cluster and grid computing |
| Soggetto topico |
Web databases
Internet searching Semantic Web |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-61324-760-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910453013603321 |
| Hauppauge, N.Y., : Nova Science Publishers, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data management in the semantic web [[electronic resource] /] / Hal Jin, editor
| Data management in the semantic web [[electronic resource] /] / Hal Jin, editor |
| Pubbl/distr/stampa | Hauppauge, N.Y., : Nova Science Publishers, c2012 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina | 025.042/7 |
| Altri autori (Persone) | JinHal |
| Collana | Distributed, cluster and grid computing |
| Soggetto topico |
Web databases
Internet searching Semantic Web |
| ISBN | 1-61324-760-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910779637803321 |
| Hauppauge, N.Y., : Nova Science Publishers, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data management in the semantic web [[electronic resource] /] / Hal Jin, editor
| Data management in the semantic web [[electronic resource] /] / Hal Jin, editor |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hauppauge, N.Y., : Nova Science Publishers, c2012 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina | 025.042/7 |
| Altri autori (Persone) | JinHal |
| Collana | Distributed, cluster and grid computing |
| Soggetto topico |
Web databases
Internet searching Semantic Web |
| ISBN | 1-61324-760-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- DATA MANAGEMENT IN THE SEMANTIC WEB -- DATA MANAGEMENT IN THE SEMANTIC WEB -- CONTENTS -- PREFACE -- Chapter1INTERPRETATIONSOFTHEWEBOFDATA -- Abstract -- 1Introduction -- 2ADistributedKnowledgeBase -- 2.1RDFSchema -- 2.2WebOntologyLanguage -- 2.3Non-AxiomaticLogic -- 2.3.1TheNon-AxiomaticLanguage -- 2.3.2TheNon-AxiomaticReasoner -- 3ADistributedMulti-RelationalNetwork -- 3.1Single-RelationalNetworks -- 3.2Multi-RelationalNetworks -- 3.3Single-RelationalNetworkAlgorithms -- 3.3.1ShortestPath -- 3.3.2Eccentricity,Radius,andDiameter -- 3.3.3ClosenessandBetweennessCentrality -- 3.3.4StationaryProbabilityDistribution -- 3.3.5PageRank -- 3.3.6SpreadingActivation -- 3.3.7AssortativeMixing -- 3.4PortingSingle-RelationalAlgorithmstotheMulti-RelationalDomain -- 3.4.1AMulti-RelationalPathAlgebra -- 3.4.2Multi-RelationalGrammarWalkers -- 4ADistributedObjectRepository -- 4.1PartialObjectRepository -- 4.2FullObjectRepository -- 4.3VirtualMachineRepository -- 5Conclusion -- Acknowledgements -- References -- Chapter 2 TOWARD SEMANTICS-AWARE WEB CRAWLING -- ABSTRACT -- 1 Introduction -- 2 Related Work -- 3 Semantics-Aware Crawler -- 3.1 Identifying Topic-Specific URLs -- 3.2 Building Training Examples -- 3.3 Ordering URLs in the Crawler's Frontier -- 4 Experimental Evaluation -- 4.1 Semantics-Aware Crawling Performance -- 5 Discussion -- 6 Conclusion -- References -- Related Terms -- Chapter3ASEMANTICTREEREPRESENTATIONFORDOCUMENTCATEGORIZATIONWITHACOMPOSITEKERNEL -- Abstract -- 1Introduction -- 2Relatedwork -- 3TheUMLSFramework -- 4DocumentModeling -- 5TheSemanticKernel -- 5.1TheMercerkernelframework -- 5.2TheUMLS-basedKernel -- 5.3TheConceptKernel -- 6ExperimentalEvaluation -- 6.1TheSVMClassifier -- 6.2TheMultinomialNaiveBayesClassifier -- 6.3Thecorpus -- 6.4Experimentalsetup -- 6.5Experimentalresults.
6.6Discussionaboutthe2007CMCMedicalNLPChallenge -- 7Conclusion -- Acknowledgments -- References -- Chapter4ONTOLOGYREUSE-ISITFEASIBLE? -- 1Introduction -- 2OntologyReuse -- 2.1ProcessOverview -- 2.2StateofPractice -- 2.3Methodologies,MethodsandTools -- 3AnEconomicModelforOntologyReuse -- 3.1AnEconomicAnalysisofOntologyReuse -- 3.2TowardsanEconomicModelforOntologyReuse -- 3.2.1TheONTOCOMmodel -- 3.2.2ExtensionsofONTOCOMforReuse -- 3.2.3CalculatingtheRelativeCostsofOntologyReuse -- 3.3ApplicationoftheModel -- 4ConclusionsandOutlook -- References -- Chapter 5 COMPUTATIONAL LOGIC AND KNOWLEDGE REPRESENTATION ISSUES IN DATA ANALYSIS FOR THE SEMANTIC WEB -- ABSTRACT -- 1 Introduction -- 2 Automated Reasoning for Ontology Engineering -- 2.1 Logical databases versus knowledge dynamism -- 3 Poor Representation and Deficient Ontologies -- 3.1 Skolem noise and poor representation -- 3.2 A special case: Semantic Mobile Web 2.0 -- 4 When is an Ontology Robust? -- 4.1 Representational perspective -- 4.2 Computational logic perspective -- 5 Lattice Categorical Theories as Robust Ontologies -- 5.1 Computational viewpoint of ontological Extensions -- 5.2 Representational perspective: Knowledge reconciliation and ontological extensions -- 5.3 Merging robust ontologies -- 5.4 Conservative retractions -- 5.5 Conservative retractions -- 6 Anomalies in Ontologies -- 6.1 Inconsistency: debugging, updating and beyond -- 6.2 Arguments, logic and trust -- 7 FOL as the Universal Provider for Formal Semantics -- 7.1 Model Theory for Semantic Web -- 8 Untrustworthy Information Versus Ontology and Knowledge -- 8.1 Mental attitudes and ontology reasoning -- 8.2 Emergent Ontologies -- 9 Understanding Ontologies: Mereotopology and Entailment-based Visualization -- 10 Meta-logical Trust -- 10.1 Extend OWL to ROWL. 10.2 Verification of Description Logics -- 11 Final Remarks -- Acknowledgments -- References -- Chapter6APPLYINGSEMANTICWEBTECHNOLOGIESTOBIOLOGICALDATAINTEGRATIONANDVISUALIZATION -- Abstract -- 1Introduction -- 2SemanticWebtechnologies -- 3SemanticWebforthelifesciences -- 3.1Biologicaldataarehugeinvolume -- 3.2Biologicaldatasourcesareheterogeneous -- 3.3Bio-ontologiesdonotfollowstandardsforontologydesign -- 3.4Biologicalknowledgeiscontextdependant -- 3.5Dataprovenanceisofcrucialimportance -- 4BiologicaldataintegrationwithSemanticWebTechnologies -- 4.1Datagathering -- 4.2Dataconversion -- 4.3OntologyofgeneratedRDFdescriptions -- 4.4PrincipeofURIsencoding -- 4.5Unificationofresources -- 4.6Ontologiesmerging -- 4.7Datarepository -- 4.8InformationretrievalwithSPARQL -- 5Datavisualization -- 6Discussion -- 7Conclusion -- References -- Chapter 7 AN ONTOLOGY AND PEER-TO-PEER BASED DATA AND SERVICE UNIFIED DISCOVERY SYSTEM -- ABSTRACT -- 1 Introduction -- 2 Preliminaries -- 2.1 Terms and definitions -- 2.2 Ontological data -- 2.2.1 Resource domain ontology -- 2.2.2 Thesaurus ontology -- 2.2.3 Service description ontology -- 2.2.4 QoS ontology -- 2.3 JXTA -- 3. Design of Unified Discovery System -- 4 Combine with JXTA -- 5. Resource registry and discovery -- 5.1. Resource registry process -- 5.2 Resource discovery process -- 5.3 Algorithms -- 5.3.1 Getting group location algorithm -- 5.3.2 Locating resource algorithm -- 5.3.3 Service matching algorithm -- 6 Implementation and Experimental Results -- 7 Related Work -- 8 Conclusion -- References -- Chapter8THEDESIGNANDDEVELOPMENTOFASEMANTICENVIRONMENTFORHOLISTICEGOVERNMENTSERVICES -- Abstract -- 1Introduction -- 2Analysisoftheproblem& -- motivation -- 3RelatedWork -- 4BusinessModel -- 5LifeEvents.Theknowledgemodel -- 6Semanticsupport -- 6.1Semantics. 6.2Applyingsemantics -- 7SupportingArchitecture -- 8LEsinmotion -- 9Conclusion -- 10Acknowledgment -- References -- Chapter 9 SEMANTIC TOPIC MODELING AND ITS APPLICATION IN BIOINFORMATICS -- ABSTRACT -- 1 Introduction -- 2 Latent Dirichlet allocation (LDA) model -- 2.1 Model specification -- 2.2 Statistical learning -- 3 Applications of LDA in biomedical research -- 3.1 Identifying biological related topics -- 3.2 Enhancing text categorization with semantic-enriched representation and training data augmentation -- 3.3 Evaluating the functional coherence of protein groups -- 4 Discussion -- Acknowledgments -- References -- Chapter 10 SUPPORTING A USER IN HIS ANNOTATION AND BROWSING ACTIVITIES IN FOLKSONOMIES -- ABSTRACT -- 1 Introduction -- 2 Preliminaries -- 2.1 Basic Definitions -- 3 Phase 1: Neighborhood Computation -- 3.1 Step 2: Construction of the sets of candidate tags starting fromTSetInput -- 3.2 Step 3: Construction of NeighTSetInput starting from the sets of candidate tags -- 4 Phase 2: Hierarchy Construction -- 4.1 The MST-based algorithm -- 4.2 The Concentric algorithm -- 5 Prototype Description -- 5.1 Class Diagram -- 5.2 Use Case and Sequence Diagrams -- 6 Experiments -- 7 Related Work -- 8 Conclusions -- References -- Chapter 11 DATA MANAGEMENT IN SENSOR NETWORKS USING SEMANTIC WEB TECHNOLOGIES -- ABSTRACT -- 1 Introduction -- 2 Sensor Networks -- 2.1 Sensor Nodes: Functionality and Characteristics -- 2.2 Sensor Networks Topologies -- 2.3 Application Areas -- 2.4 Sensor Web: Data and Services in a Sensor Network -- 3 Knowledge Management in Sensor Networks -- 3.1 Current Approaches -- 3.2 A Unifying Generic Architecture for Sensor Data Management -- 3.2.1 Data Layer -- 3.2.2 Processing Layer -- 3.2.3 Semantic Layer -- 3.2.4 Use Case Scenario. 4 Conclusions - Open Issues -- References -- Chapter 12 CHINESE SEMANTIC DEPENDENCY ANALYSIS -- ABSTRACT -- 1 Introduction -- 2 Semantic Annotation -- Semantic Role Labeling -- Semantic Dependency Analysis -- 3 Chinese Semantic Dependency Corpus and Tag Set -- 4 Semantic Dependency Relation Classification -- Mutli-Classifier Classification -- Classification Features -- Rule-Based Correction -- 5 Experimental Results -- 6 The SEEN System -- Syntatic Analysis Module -- Headword Assignment Module -- Semantic Dependency Assignment Module -- 7 Conclusion -- References -- Chapter 13 CREATING PERSONAL CONTENT MANAGEMENT SYSTEMS USING SEMANTIC WEB TECHNOLOGIES -- ABSTRACT -- 1 Introduction -- 2 Related Work -- 3 PCMS Metadata Model -- 3.1 Content-independent metadata -- 3.1.1 System Metadata -- 3.1.2 Security Metadata -- 3.1.3 User Metadata -- 3.2 Image-related Metadata -- 4 Semantic PCMS -- 4.1 Interoperability Issues -- 4.2 Semantic Metadata Model -- 4.3 Lower layer -- 4.4 Mapping and rules -- 5 Metadata Service -- 5.1 Metadata Management -- 5.2 XML to RDF Conversion -- 6 Use Case Scenario -- 6.1 Solving the Use Case Scenario with the Proposed System -- 6.2 Solving the Use Case Scenario with the Related Work -- 7 Conclusion -- 8 Acknowledgments -- References -- Chapter 14 A HYBRID DATA LAYER TO UTILIZE OPEN CONTENT FOR HIGHER-LAYERED APPLICATIONS -- ABSTRACT -- 1 Introduction -- Resources and Open Content -- Web 3.0 alias Social Semantic Web behind the scenes -- 2 How to Utilize Open Content for Higher-layered Applications? -- 3. State of the Art and Related Work -- 4 qKAI Application Framework -- qKAI system layer -- Data storage and change management -- Discovering Linked Data by setting Points of Interest -- SQL replaces SPARQL -- Hybrid knowledge index -- Change management. Reusability and extensibility. |
| Record Nr. | UNINA-9910825006303321 |
| Hauppauge, N.Y., : Nova Science Publishers, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital research confidential : the secrets of studying behavior online / / Hargittai, Eszter, and Christian Sandvig, eds
| Digital research confidential : the secrets of studying behavior online / / Hargittai, Eszter, and Christian Sandvig, eds |
| Pubbl/distr/stampa | Cambridge, Massachusetts : , : The MIT Press, , 2016 |
| Descrizione fisica | 1 online resource (287 p.) |
| Disciplina | 302.30285 |
| Soggetto topico |
Social sciences - Research
Social networks - Research Internet searching Social scientists - Attitudes |
| Soggetto genere / forma | Electronic books. |
| ISBN | 0-262-33122-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- How to think about digital research / Christian Sandvig and Eszter Hargittai -- "How local is user-generated content" : a 9,000+ word essay on answering a five-word research question" : or how we learned to stop worrying (or worry less) and love the diverse challenges of our fast-moving, geographically-flavored interdisciplinary research area / Darren Gergle and Brent Hecht -- Flash mobs and the social life of public spaces : analyzing online visual data to study new forms of sociability / Virag Molnar and Aron Hsiao -- Social software as social science / Eric Gilbert and Karrie Karahalios -- Hired hands and dubious guesses : adventures in crowdsourced data collection / Aaron Shaw -- Making sense of teen life : strategies for capturing ethnographic data in a networked era / Danah Boyd -- When should we use real names in published accounts of internet research? / Amy Bruckman, Kurt Luther, and Casey Fiesler -- The art of web crawling for social science research / Michelle Shumate and Matthew Weber -- The ethnographic study of visual culture in the age of digitization / Paul Leonardi -- Read/write the digital archive: strategies for historical web research / Megan Sapnar Ankerson -- Big data, big problems, big opportunities : using internet log data to conduct social network analysis research / Brooke Foucault Welles -- Contributors -- References -- Index. |
| Record Nr. | UNINA-9910460647603321 |
| Cambridge, Massachusetts : , : The MIT Press, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Soggetto topico
-
Internet searching
(106)
- Web search engines (24)
- Data mining (18)
- Search engines (12)
- Internet marketing (9)