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Knowledge Representation

This collection of extended versions of 12 papers from the First International Conference on Principles of Knowledge Representation and;

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Handbook of Knowledge Representation

of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety;

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Graph Structures for Knowledge Representation and Reasoning

for Knowledge Representation and Reasoning, GKR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European;

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Graph Structures for Knowledge Representation and Reasoning

Knowledge Representation and Reasoning, GKR 2017, held in Melbourne, VIC, Australia, in August 2017, associated with IJCAI 2017, the 26th;

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Graph Structures for Knowledge Representation and Reasoning

Knowledge Representation and Reasoning, GKR 2015, held in Buenos Aires, Argentina, in July 2015, associated with IJCAI 2015, the 24th International;

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Graph Structures for Knowledge Representation and Reasoning

Knowledge Representation and Reasoning, GKR 2013, held in Beijing, China, in August 2013, associated with IJCAI 2013, the 23rd International Joint;

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Knowledge Representation Reasoning & The

Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge;

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AAAI-90

System Design Methodologies: techniques for designing expert systems and acquiring domain knowledge. Knowledge Representation: knowledge;

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Conceptual Structures: From Information to Intelligence

held in Europe, A- tralia, and North America since 1993. The focus of the conference has been the representation and analysis of conceptual;

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Graph-based Knowledge Representation

This book provides a de?nition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while;

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Knowledge Representation and Reasoning

last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and;

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Logic Programming and Nonmonotonic Reasoning

reasoning, and knowledge representation, the conference aims to facilitate interactions between those researchers and practitioners interested;

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Logic Programming and Nonmonotonic Reasoning

knowledge representation. The aim of the LPNMR conferences is to facilitate interactions between researchers interested in the design and;

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Graph-Based Representation and Reasoning

, in July 2014. The 17 regular papers and 6 short papers presented in this volume were carefully reviewed and selected from 40 and 10 submissions;

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Semantic Knowledge Representation for Information Retrieval

of formal knowledge representation and reasoning. The methodologies included combine the specifics of indexing languages, Web representation;

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Logic Programming and Nonmonotonic Reasoning

reasoning and knowledge representation. The aim of the c- ference is to facilitate interaction between researchers interested in the design and;

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MDATA: A New Knowledge Representation Model

Knowledge representation is an important task in understanding how humans think and learn. Although many representation models or cognitive;

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Knowledge Representation, Reasoning and Declarative Problem Solving

giving them the ability to express knowledge and reason about it. He presents a language, AnsProlog, for both knowledge representation and;

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Knowledge Representation, Reasoning and Declarative Problem Solving

giving them the ability to express knowledge and reason about it. He presents a language, AnsProlog, for both knowledge representation and;

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Conceptual Structures: Leveraging Semantic Technologies

knowledge representation and reasoning with conceptual graphs, over the years ICCS has broadened its scope to include in- vations from a wider range;

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Logic Programming and Nonmonotonic Reasoning

complexity; knowledge representation and reasoning; and systems.;

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PRICAI 2021: Trends in Artificial Intelligence

representation and reasoning, planning and scheduling, computer vision, distributed artificial intelligence, search methodologies, etc. Part I includes;

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Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding

wide research fields including the knowledge graph, the semantic Web, linked data, NLP, information extraction, knowledge representation and;

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Open Semantic Technologies for Intelligent System

representation and reasoning, semantic networks, natural language processing, temporal reasoning, probabilistic reasoning, multi-agent systems;

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Domain Ontologies for Reasoning Machines in Factory Automation

processes. This book targets the topic of knowledge representation and reasoning machines and introduces the concept of domain ontologies. Domain;

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Thinking with Diagrams

world of diagrams and diagrammatic representation in thought experiments and/or processes, manifested in forms as divers as notes, tables;

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Knowledge Science, Engineering and Management

knowledge representation and reasoning.;

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