Conceptual Structures: Logical, Linguistic, and Computational Issues: 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000. Proceedings
Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer models are formed through the interaction of...
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description | Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di?erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (?rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di?erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di?erent cognitive processes lead to the opening of the ?eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge. |
doi_str_mv | 10.1007/10722280 |
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Proceedings</title><source>Springer Books</source><creator>Ganter, Bernhard ; Mineau, Guy W</creator><contributor>Ganter, Bernhard ; Mineau, Guy W.</contributor><creatorcontrib>Ganter, Bernhard ; Mineau, Guy W ; SpringerLink (Online service) ; Ganter, Bernhard ; Mineau, Guy W.</creatorcontrib><description>Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di?erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (?rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di?erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di?erent cognitive processes lead to the opening of the ?eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. 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Proceedings</title><description>Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di?erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (?rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di?erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di?erent cognitive processes lead to the opening of the ?eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge.</description><subject>Algorithm Analysis and Problem Complexity</subject><subject>Artificial Intelligence</subject><subject>Computation by Abstract Devices</subject><subject>Computational complexity</subject><subject>Computer Science</subject><subject>Computer software</subject><subject>Conceptual structures (Information theory)</subject><subject>Discrete Mathematics in Computer Science</subject><subject>Graph theory</subject><subject>Information theory</subject><subject>Knowledge representation (Information theory)</subject><subject>Logic diagrams</subject><subject>Mathematical Logic and Formal Languages</subject><subject>Natural language processing (Computer science)</subject><subject>Theory of Computation</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3662198762</isbn><isbn>354067859X</isbn><isbn>9783662198766</isbn><isbn>9783540678595</isbn><isbn>9783540446637</isbn><isbn>354044663X</isbn><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2000</creationdate><recordtype>book</recordtype><sourceid/><recordid>eNptkMtKw0AUhscbWGvBR8hKEBqdmTNXdyXeCgEXitswnUza2JgpmUn18Y1UF0LP5sDh-384H0IXBF8TjOUNwZJSqvABmmipgDPMmBAgD9GICEJSAKaP0BkIQYlWUtBjNMKAaaolg1M0CeEdDwNDCVYjdJf51rpN7E2TvMSut7HvXLhNcr-srWmmSV63y74OsbbTxLRlkvmPTR9NrH07ROYh9C6co5PKNMFNfvcYvT3cv2ZPaf78OM9meWoIA_mVSs0dLwUWQvFFaZ3SnGCwbkE1WFCGVJxbx5gyFRACminMS1ppoctyOFsYo6tdsQlr9xlWvomh2DZu4f06FP98DOzljg2bbvjBdcWOIrj4EVn8iRzAdA9oOruqt24P_w3AdGxy</recordid><startdate>2000</startdate><enddate>2000</enddate><creator>Ganter, Bernhard</creator><creator>Mineau, Guy W</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope/></search><sort><creationdate>2000</creationdate><title>Conceptual Structures: Logical, Linguistic, and Computational Issues</title><author>Ganter, Bernhard ; Mineau, Guy W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a1437x-795e5d606685bdce895103ceb293c38a1f55ce448af311394805d2f969dde44c3</frbrgroupid><rsrctype>books</rsrctype><prefilter>books</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Algorithm Analysis and Problem Complexity</topic><topic>Artificial Intelligence</topic><topic>Computation by Abstract Devices</topic><topic>Computational complexity</topic><topic>Computer Science</topic><topic>Computer software</topic><topic>Conceptual structures (Information theory)</topic><topic>Discrete Mathematics in Computer Science</topic><topic>Graph theory</topic><topic>Information theory</topic><topic>Knowledge representation (Information theory)</topic><topic>Logic diagrams</topic><topic>Mathematical Logic and Formal Languages</topic><topic>Natural language processing (Computer science)</topic><topic>Theory of Computation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ganter, Bernhard</creatorcontrib><creatorcontrib>Mineau, Guy W</creatorcontrib><creatorcontrib>SpringerLink (Online service)</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ganter, Bernhard</au><au>Mineau, Guy W</au><au>Ganter, Bernhard</au><au>Mineau, Guy W.</au><aucorp>SpringerLink (Online service)</aucorp><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>Conceptual Structures: Logical, Linguistic, and Computational Issues: 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000. Proceedings</btitle><seriestitle>Lecture Notes in Artificial Intelligence</seriestitle><date>2000</date><risdate>2000</risdate><volume>1867</volume><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3662198762</isbn><isbn>354067859X</isbn><isbn>9783662198766</isbn><isbn>9783540678595</isbn><eisbn>9783540446637</eisbn><eisbn>354044663X</eisbn><abstract>Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di?erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (?rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di?erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di?erent cognitive processes lead to the opening of the ?eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/10722280</doi><tpages>XII, 576</tpages></addata></record> |
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subjects | Algorithm Analysis and Problem Complexity Artificial Intelligence Computation by Abstract Devices Computational complexity Computer Science Computer software Conceptual structures (Information theory) Discrete Mathematics in Computer Science Graph theory Information theory Knowledge representation (Information theory) Logic diagrams Mathematical Logic and Formal Languages Natural language processing (Computer science) Theory of Computation |
title | Conceptual Structures: Logical, Linguistic, and Computational Issues: 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000. Proceedings |
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