Knowledge grid: toward cyber-physical society
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Format: | Elektronisch E-Book |
Sprache: | English |
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Singapore
World Scientific
©2012
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Ausgabe: | 2nd ed |
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Online-Zugang: | Volltext |
Beschreibung: | Previous edition published in 2004 Includes bibliographical references and index The Knowledge Grid is an intelligent and sustainable interaction environment that consists of autonomous individuals, self-organized semantic communities, adaptive networking mechanisms, evolving semantic link networks keeping meaningful connection between individuals, flows for dynamic resource sharing, and mechanisms supporting effective resource management and providing appropriate knowledge services for learning, innovation, teamwork, problem solving, and decision making. This book presents its methodology, theory, models and applications systematically for the first time. Its second editio 1. The knowledge grid methodology. 1.1. The knowledge space -- Knowledge as a space. 1.2. The cyber space. 1.3. Effort toward the intelligent interconnection environment. 1.4. Challenge and opportunity. 1.5. The knowledge grid environment. 1.6. Epistemology and knowledge. 1.7. Ontology. 1.8. System methodology. 1.9. Dynamic knowledge management. 1.10. The knowledge grid as a research area -- - 2. The semantic link network. 2.1. The idea of mapping. 2.2. Basic concepts and characteristics. 2.3. Relational reasoning and the semantic space. 2.4. An algebraic model of the SLN. 2.5. SLN normalization. 2.6. Constraints and displaying. 2.7. SLN ranking. 2.8. Implementation of SLN operations. 2.9. SLN analogical reasoning. 2.10. Dynamic SLN. 2.11. SLN abstraction. 2.12. Application: SLN-based image retrieval. 2.13. Application: Active Document Framework (ADF). 2.14. Application: e-learning. 2.15. Potential applications, relevant work and Q & A. 2.16. SLN 2.0: Autonomous semantic data model. 2.17. Probabilistic semantic link network. 2.18. Discovering semantic link network. 2.19. SLN 3.0: Cyber-physical-socio-mental network. 2.20. Principles of mental concepts. 2.21. Discussion: philosophy, language and semantics -- - 3. A resource space model. 3.1. Examples of using multi-dimensional classifications. 3.2. The virtual grid. 3.3. The Resource Space Model (RSM). 3.4. Criteria for designing resource spaces. 3.5. Designing resource spaces. 3.6. Representation of resources. 3.7. The Resource Using Mechanism (RUM). 3.8. Comparisons. 3.9. Dealing with exponential growth of resources. 3.10. Extension of the resource space model. 3.11. Integrity constraint for the resource space model. 3.12. Storage for resource space and adaptability. 3.13. Application: faceted navigation. 3.14. Application: faceted navigation. 3.14. Application: personal resource space. 3.15. The dimension -- - 4. The single semantic image. 4.1. Obtaining single semantic image from multi-facet views. 4.2. Combining SLN and RSM. 4.3. The SSeI mechanism. 4.4. The single semantic image query language. 4.5. SSeIQL syntax specification. 4.6. The programming environment. 4.7. The single semantic image browser. 4.8. The SSeI in a peer-to-peer semantic link network. 4.9. Abstraction level, time, epistemology, location and space. 4.10. A semantic lens. 4.11. A semantic lens for text visualization. 4.12. Single semantic image through multiple channels. 4.13. Philosophical discussion -- 5. Knowledge flow. 5.1. Concept. 5.2. A knowledge flow process model. 5.3. Peer-to-peer knowledge sharing. 5.4. Knowledge intensity. 5.5. Knowledge flow principles. 5.6. Computational model of knowledge intensity. 5.7. Knowledge spiral model. 5.8. Knowledge flow network planning. 5.9. Resource-mediated knowledge flows. 5.10. Exploring knowledge flows Exploring scale-free network. 6.1. Concepts. 6.2. The topologies of some real networks. 6.3. Random graph theory. 6.4. The small-world theory. 6.5. Modeling measures for live scale-free networks. 6.6. Modeling actual scale-free network. 6.7. Summary and implications -- 7. Topological centrality in social network. 7.1. Principles of influence. 7.2. Basic concept. 7.3. Calculating topological centrality. 7.4. Discovering research communities. 7.5. Discovering backbone in research network. 7.6. Discussion -- 8. Decentralized peer-to-peer recommendation and query. 8.2. Basic idea and architecture. 8.3. Semantic links for peer-to-peer networking. 8.4. Communities in P2P-SLN. 8.5. Routing strategies and process. 8.6. Self-organization of communities and evolution. 8.7. Application and experiment. 8.8. Performance of P2P-SLN. 8.9. Incorporating recommendation. 8.10. Toward P2P knowledge flow networking -- 9. P2P semantic overlay networks. 9.1. Structure approaches. 9.2. Unstructured approaches. 9.3. Discussion -- 10. The energy-knowledge grid. 10.1. The knowledge grid meets the smart grid. 10.2. Architecture and characteristics. 10.3. Multi-dimensional devices and requirements. 10.4. Multi-layer complex networks |
Beschreibung: | 1 Online-Ressource (xv, 506 pages) |
ISBN: | 9789814291781 9814291781 9789814439954 9814439959 9814291773 9789814291774 |
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500 | |a The Knowledge Grid is an intelligent and sustainable interaction environment that consists of autonomous individuals, self-organized semantic communities, adaptive networking mechanisms, evolving semantic link networks keeping meaningful connection between individuals, flows for dynamic resource sharing, and mechanisms supporting effective resource management and providing appropriate knowledge services for learning, innovation, teamwork, problem solving, and decision making. This book presents its methodology, theory, models and applications systematically for the first time. Its second editio | ||
500 | |a 1. The knowledge grid methodology. 1.1. The knowledge space -- Knowledge as a space. 1.2. The cyber space. 1.3. Effort toward the intelligent interconnection environment. 1.4. Challenge and opportunity. 1.5. The knowledge grid environment. 1.6. Epistemology and knowledge. 1.7. Ontology. 1.8. System methodology. 1.9. Dynamic knowledge management. 1.10. The knowledge grid as a research area -- | ||
500 | |a - 2. The semantic link network. 2.1. The idea of mapping. 2.2. Basic concepts and characteristics. 2.3. Relational reasoning and the semantic space. 2.4. An algebraic model of the SLN. 2.5. SLN normalization. 2.6. Constraints and displaying. 2.7. SLN ranking. 2.8. Implementation of SLN operations. 2.9. SLN analogical reasoning. 2.10. Dynamic SLN. 2.11. SLN abstraction. 2.12. Application: SLN-based image retrieval. 2.13. Application: Active Document Framework (ADF). 2.14. Application: e-learning. 2.15. Potential applications, relevant work and Q & A. 2.16. SLN 2.0: Autonomous semantic data model. 2.17. Probabilistic semantic link network. 2.18. Discovering semantic link network. 2.19. SLN 3.0: Cyber-physical-socio-mental network. 2.20. Principles of mental concepts. 2.21. Discussion: philosophy, language and semantics -- | ||
500 | |a - 3. A resource space model. 3.1. Examples of using multi-dimensional classifications. 3.2. The virtual grid. 3.3. The Resource Space Model (RSM). 3.4. Criteria for designing resource spaces. 3.5. Designing resource spaces. 3.6. Representation of resources. 3.7. The Resource Using Mechanism (RUM). 3.8. Comparisons. 3.9. Dealing with exponential growth of resources. 3.10. Extension of the resource space model. 3.11. Integrity constraint for the resource space model. 3.12. Storage for resource space and adaptability. 3.13. Application: faceted navigation. 3.14. Application: faceted navigation. 3.14. Application: personal resource space. 3.15. The dimension -- | ||
500 | |a - 4. The single semantic image. 4.1. Obtaining single semantic image from multi-facet views. 4.2. Combining SLN and RSM. 4.3. The SSeI mechanism. 4.4. The single semantic image query language. 4.5. SSeIQL syntax specification. 4.6. The programming environment. 4.7. The single semantic image browser. 4.8. The SSeI in a peer-to-peer semantic link network. 4.9. Abstraction level, time, epistemology, location and space. 4.10. A semantic lens. 4.11. A semantic lens for text visualization. 4.12. Single semantic image through multiple channels. 4.13. Philosophical discussion -- 5. Knowledge flow. 5.1. Concept. 5.2. A knowledge flow process model. 5.3. Peer-to-peer knowledge sharing. 5.4. Knowledge intensity. 5.5. Knowledge flow principles. 5.6. Computational model of knowledge intensity. 5.7. Knowledge spiral model. 5.8. Knowledge flow network planning. 5.9. Resource-mediated knowledge flows. 5.10. Exploring knowledge flows | ||
500 | |a Exploring scale-free network. 6.1. Concepts. 6.2. The topologies of some real networks. 6.3. Random graph theory. 6.4. The small-world theory. 6.5. Modeling measures for live scale-free networks. 6.6. Modeling actual scale-free network. 6.7. Summary and implications -- 7. Topological centrality in social network. 7.1. Principles of influence. 7.2. Basic concept. 7.3. Calculating topological centrality. 7.4. Discovering research communities. 7.5. Discovering backbone in research network. 7.6. Discussion -- 8. Decentralized peer-to-peer recommendation and query. 8.2. Basic idea and architecture. 8.3. Semantic links for peer-to-peer networking. 8.4. Communities in P2P-SLN. 8.5. Routing strategies and process. 8.6. Self-organization of communities and evolution. 8.7. Application and experiment. 8.8. Performance of P2P-SLN. 8.9. Incorporating recommendation. 8.10. Toward P2P knowledge flow networking -- 9. P2P semantic overlay networks. 9.1. Structure approaches. 9.2. Unstructured approaches. 9.3. Discussion -- 10. The energy-knowledge grid. 10.1. The knowledge grid meets the smart grid. 10.2. Architecture and characteristics. 10.3. Multi-dimensional devices and requirements. 10.4. Multi-layer complex networks | ||
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Datensatz im Suchindex
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---|---|
any_adam_object | |
author | Zhuge, Hai |
author_facet | Zhuge, Hai |
author_role | aut |
author_sort | Zhuge, Hai |
author_variant | h z hz |
building | Verbundindex |
bvnumber | BV042969191 |
collection | ZDB-4-EBA ZDB-4-EBU |
ctrlnum | (OCoLC)815693338 (DE-599)BVBBV042969191 |
dewey-full | 004.678 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 004 - Computer science |
dewey-raw | 004.678 |
dewey-search | 004.678 |
dewey-sort | 14.678 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
edition | 2nd ed |
format | Electronic eBook |
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A knowledge flow process model. 5.3. Peer-to-peer knowledge sharing. 5.4. Knowledge intensity. 5.5. Knowledge flow principles. 5.6. Computational model of knowledge intensity. 5.7. Knowledge spiral model. 5.8. Knowledge flow network planning. 5.9. Resource-mediated knowledge flows. 5.10. Exploring knowledge flows</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Exploring scale-free network. 6.1. Concepts. 6.2. The topologies of some real networks. 6.3. Random graph theory. 6.4. The small-world theory. 6.5. Modeling measures for live scale-free networks. 6.6. Modeling actual scale-free network. 6.7. Summary and implications -- 7. Topological centrality in social network. 7.1. Principles of influence. 7.2. Basic concept. 7.3. Calculating topological centrality. 7.4. Discovering research communities. 7.5. Discovering backbone in research network. 7.6. Discussion -- 8. Decentralized peer-to-peer recommendation and query. 8.2. Basic idea and architecture. 8.3. Semantic links for peer-to-peer networking. 8.4. Communities in P2P-SLN. 8.5. Routing strategies and process. 8.6. Self-organization of communities and evolution. 8.7. Application and experiment. 8.8. Performance of P2P-SLN. 8.9. Incorporating recommendation. 8.10. Toward P2P knowledge flow networking -- 9. P2P semantic overlay networks. 9.1. Structure approaches. 9.2. Unstructured approaches. 9.3. Discussion -- 10. The energy-knowledge grid. 10.1. The knowledge grid meets the smart grid. 10.2. Architecture and characteristics. 10.3. Multi-dimensional devices and requirements. 10.4. 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id | DE-604.BV042969191 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T07:14:03Z |
institution | BVB |
isbn | 9789814291781 9814291781 9789814439954 9814439959 9814291773 9789814291774 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028395058 |
oclc_num | 815693338 |
open_access_boolean | |
owner | DE-1046 DE-1047 |
owner_facet | DE-1046 DE-1047 |
physical | 1 Online-Ressource (xv, 506 pages) |
psigel | ZDB-4-EBA ZDB-4-EBU FAW_PDA_EBA FLA_PDA_EBU |
publishDate | 2012 |
publishDateSearch | 2012 |
publishDateSort | 2012 |
publisher | World Scientific |
record_format | marc |
spelling | Zhuge, Hai Verfasser aut Knowledge grid toward cyber-physical society Hai Zhuge 2nd ed Singapore World Scientific ©2012 1 Online-Ressource (xv, 506 pages) txt rdacontent c rdamedia cr rdacarrier Previous edition published in 2004 Includes bibliographical references and index The Knowledge Grid is an intelligent and sustainable interaction environment that consists of autonomous individuals, self-organized semantic communities, adaptive networking mechanisms, evolving semantic link networks keeping meaningful connection between individuals, flows for dynamic resource sharing, and mechanisms supporting effective resource management and providing appropriate knowledge services for learning, innovation, teamwork, problem solving, and decision making. This book presents its methodology, theory, models and applications systematically for the first time. Its second editio 1. The knowledge grid methodology. 1.1. The knowledge space -- Knowledge as a space. 1.2. The cyber space. 1.3. Effort toward the intelligent interconnection environment. 1.4. Challenge and opportunity. 1.5. The knowledge grid environment. 1.6. Epistemology and knowledge. 1.7. Ontology. 1.8. System methodology. 1.9. Dynamic knowledge management. 1.10. The knowledge grid as a research area -- - 2. The semantic link network. 2.1. The idea of mapping. 2.2. Basic concepts and characteristics. 2.3. Relational reasoning and the semantic space. 2.4. An algebraic model of the SLN. 2.5. SLN normalization. 2.6. Constraints and displaying. 2.7. SLN ranking. 2.8. Implementation of SLN operations. 2.9. SLN analogical reasoning. 2.10. Dynamic SLN. 2.11. SLN abstraction. 2.12. Application: SLN-based image retrieval. 2.13. Application: Active Document Framework (ADF). 2.14. Application: e-learning. 2.15. Potential applications, relevant work and Q & A. 2.16. SLN 2.0: Autonomous semantic data model. 2.17. Probabilistic semantic link network. 2.18. Discovering semantic link network. 2.19. SLN 3.0: Cyber-physical-socio-mental network. 2.20. Principles of mental concepts. 2.21. Discussion: philosophy, language and semantics -- - 3. A resource space model. 3.1. Examples of using multi-dimensional classifications. 3.2. The virtual grid. 3.3. The Resource Space Model (RSM). 3.4. Criteria for designing resource spaces. 3.5. Designing resource spaces. 3.6. Representation of resources. 3.7. The Resource Using Mechanism (RUM). 3.8. Comparisons. 3.9. Dealing with exponential growth of resources. 3.10. Extension of the resource space model. 3.11. Integrity constraint for the resource space model. 3.12. Storage for resource space and adaptability. 3.13. Application: faceted navigation. 3.14. Application: faceted navigation. 3.14. Application: personal resource space. 3.15. The dimension -- - 4. The single semantic image. 4.1. Obtaining single semantic image from multi-facet views. 4.2. Combining SLN and RSM. 4.3. The SSeI mechanism. 4.4. The single semantic image query language. 4.5. SSeIQL syntax specification. 4.6. The programming environment. 4.7. The single semantic image browser. 4.8. The SSeI in a peer-to-peer semantic link network. 4.9. Abstraction level, time, epistemology, location and space. 4.10. A semantic lens. 4.11. A semantic lens for text visualization. 4.12. Single semantic image through multiple channels. 4.13. Philosophical discussion -- 5. Knowledge flow. 5.1. Concept. 5.2. A knowledge flow process model. 5.3. Peer-to-peer knowledge sharing. 5.4. Knowledge intensity. 5.5. Knowledge flow principles. 5.6. Computational model of knowledge intensity. 5.7. Knowledge spiral model. 5.8. Knowledge flow network planning. 5.9. Resource-mediated knowledge flows. 5.10. Exploring knowledge flows Exploring scale-free network. 6.1. Concepts. 6.2. The topologies of some real networks. 6.3. Random graph theory. 6.4. The small-world theory. 6.5. Modeling measures for live scale-free networks. 6.6. Modeling actual scale-free network. 6.7. Summary and implications -- 7. Topological centrality in social network. 7.1. Principles of influence. 7.2. Basic concept. 7.3. Calculating topological centrality. 7.4. Discovering research communities. 7.5. Discovering backbone in research network. 7.6. Discussion -- 8. Decentralized peer-to-peer recommendation and query. 8.2. Basic idea and architecture. 8.3. Semantic links for peer-to-peer networking. 8.4. Communities in P2P-SLN. 8.5. Routing strategies and process. 8.6. Self-organization of communities and evolution. 8.7. Application and experiment. 8.8. Performance of P2P-SLN. 8.9. Incorporating recommendation. 8.10. Toward P2P knowledge flow networking -- 9. P2P semantic overlay networks. 9.1. Structure approaches. 9.2. Unstructured approaches. 9.3. Discussion -- 10. The energy-knowledge grid. 10.1. The knowledge grid meets the smart grid. 10.2. Architecture and characteristics. 10.3. Multi-dimensional devices and requirements. 10.4. Multi-layer complex networks COMPUTERS / Networking / Intranets & Extranets bisacsh COMPUTERS / Web / General bisacsh Knowledge management fast Semantic integration (Computer systems) fast Semantic networks (Information theory) fast Knowledge management Semantic integration (Computer systems) Semantic networks (Information theory) Wissensmanagement (DE-588)4561842-2 gnd rswk-swf Semantic Web (DE-588)4688372-1 gnd rswk-swf Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd rswk-swf Semantisches Netz (DE-588)4242662-5 gnd rswk-swf Semantisches Netz (DE-588)4242662-5 s 1\p DE-604 Semantic Web (DE-588)4688372-1 s 2\p DE-604 Mensch-Maschine-Kommunikation (DE-588)4125909-9 s 3\p DE-604 Wissensmanagement (DE-588)4561842-2 s 4\p DE-604 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=503425 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Zhuge, Hai Knowledge grid toward cyber-physical society COMPUTERS / Networking / Intranets & Extranets bisacsh COMPUTERS / Web / General bisacsh Knowledge management fast Semantic integration (Computer systems) fast Semantic networks (Information theory) fast Knowledge management Semantic integration (Computer systems) Semantic networks (Information theory) Wissensmanagement (DE-588)4561842-2 gnd Semantic Web (DE-588)4688372-1 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Semantisches Netz (DE-588)4242662-5 gnd |
subject_GND | (DE-588)4561842-2 (DE-588)4688372-1 (DE-588)4125909-9 (DE-588)4242662-5 |
title | Knowledge grid toward cyber-physical society |
title_auth | Knowledge grid toward cyber-physical society |
title_exact_search | Knowledge grid toward cyber-physical society |
title_full | Knowledge grid toward cyber-physical society Hai Zhuge |
title_fullStr | Knowledge grid toward cyber-physical society Hai Zhuge |
title_full_unstemmed | Knowledge grid toward cyber-physical society Hai Zhuge |
title_short | Knowledge grid |
title_sort | knowledge grid toward cyber physical society |
title_sub | toward cyber-physical society |
topic | COMPUTERS / Networking / Intranets & Extranets bisacsh COMPUTERS / Web / General bisacsh Knowledge management fast Semantic integration (Computer systems) fast Semantic networks (Information theory) fast Knowledge management Semantic integration (Computer systems) Semantic networks (Information theory) Wissensmanagement (DE-588)4561842-2 gnd Semantic Web (DE-588)4688372-1 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Semantisches Netz (DE-588)4242662-5 gnd |
topic_facet | COMPUTERS / Networking / Intranets & Extranets COMPUTERS / Web / General Knowledge management Semantic integration (Computer systems) Semantic networks (Information theory) Wissensmanagement Semantic Web Mensch-Maschine-Kommunikation Semantisches Netz |
url | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=503425 |
work_keys_str_mv | AT zhugehai knowledgegridtowardcyberphysicalsociety |