Graph based Knowledge Representation

Author: Michel Chein
Publisher: Springer Science & Business Media
ISBN: 1848002866
Format: PDF, Mobi
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This book provides a de?nition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while focusing on the com- tational properties of this formalism. Knowledge can be symbolically represented in many ways. The knowledge representation and reasoning formalism presented here is a graph formalism – knowledge is represented by labeled graphs, in the graph theory sense, and r- soning mechanisms are based on graph operations, with graph homomorphism at the core. This formalism can thus be considered as related to semantic networks. Since their conception, semantic networks have faded out several times, but have always returned to the limelight. They faded mainly due to a lack of formal semantics and the limited reasoning tools proposed. They have, however, always rebounded - cause labeled graphs, schemas and drawings provide an intuitive and easily und- standable support to represent knowledge. This formalism has the visual qualities of any graphic model, and it is logically founded. This is a key feature because logics has been the foundation for knowledge representation and reasoning for millennia. The authors also focus substantially on computational facets of the presented formalism as they are interested in knowledge representation and reasoning formalisms upon which knowledge-based systems can be built to solve real problems. Since object structures are graphs, naturally graph homomorphism is the key underlying notion and, from a computational viewpoint, this moors calculus to combinatorics and to computer science domains in which the algorithmicqualitiesofgraphshavelongbeenstudied,asindatabasesandconstraint networks.

Graph Structures for Knowledge Representation and Reasoning

Author: Madalina Croitoru
Publisher: Springer
ISBN: 3319045342
Format: PDF, Docs
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This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2013, held in Beijing, China, in August 2013, associated with IJCAI 2013, the 23rd International Joint Conference on Artificial Intelligence. The 12 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers feature current research involved in the development and application of graph-based knowledge representation formalisms and reasoning techniques. They address the following topics: representations of constraint satisfaction problems; formal concept analysis; conceptual graphs; and argumentation frameworks.

Graph Based Representation and Reasoning

Author: Ollivier Haemmerlé
Publisher: Springer
ISBN: 3319409859
Format: PDF, Mobi
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This book constitutes the proceedings of the 22th International Conference on Conceptual Structures, ICCS 2016, held in Annecy, France, in July 2016. The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 40 submissions. They are organized around the following topical sections: time representation; graphs and networks; formal concept analysis; ontologies and linked data.

Conceptual Structures for Discovering Knowledge

Author: Heather D. Pfeiffer
Publisher: Springer
ISBN: 3642357865
Format: PDF, ePub, Docs
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This book constitutes the proceedings of the 20th International Conference on Conceptual Structures, ICCS 2013, held in Mumbai, India, in January 2013. The 22 full papers presented were carefully reviewed and selected from 43 submissions for inclusion in the book. The volume also contains 3 invited talks. ICCS focuses on the useful representation and analysis of conceptual knowledge with research and business applications. It advances the theory and practice in connecting the user's conceptual approach to problem solving with the formal structures that computer applications need to bring their productivity to bear. Conceptual structures (CS) represent a family of approaches that builds on the successes of artificial intelligence, business intelligence, computational linguistics, conceptual modeling, information and Web technologies, user modeling, and knowledge management.

Handbook of Knowledge Representation

Author: Frank van Harmelen
Publisher: Elsevier
ISBN: 9780080557021
Format: PDF, Kindle
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Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter * Handle qualitative and uncertain information * Improve computational tractability to solve your problems easily

Advanced Methods for Knowledge Discovery from Complex Data

Author: Ujjwal Maulik
Publisher: Springer Science & Business Media
ISBN: 1846282845
Format: PDF, Kindle
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The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.

Exploiting Linked Data and Knowledge Graphs in Large Organisations

Author: Jeff Z. Pan
Publisher: Springer
ISBN: 3319456547
Format: PDF, Docs
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This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and “standard” data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.

Representation and Management of Narrative Information

Author: Gian Piero Zarri
Publisher: Springer Science & Business Media
ISBN: 9781848000780
Format: PDF, ePub
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A big amount of important, ‘economically relevant’ information, is buried within the huge mass of multimedia documents that correspond to some form of ‘narrative’ description. Due to the ubiquity of these ‘narrative’ resources, being able to represent in a general, accurate, and effective way their semantic content – i.e., their key ‘meaning’ – is then both conceptually relevant and economically important. In this book, we present the main properties of NKRL (‘Narrative Knowledge Representation Language’), a language expressly designed for representing, in a standardised way, the ‘meaning’ of complex multimedia narrative documents. NKRL is a fully implemented language/environment. The software exists in two versions, an ORACLE-supported version and a file-oriented one. Written from a multidisciplinary perspective, this exhaustive description of NKRL and of the associated knowledge representation principles will be an invaluable source of reference for practitioners, researchers, and graduates.

Knowledge Representation and Metaphor

Author: E. Cornell Way
Publisher: Springer Science & Business Media
ISBN: 9401579415
Format: PDF, Docs
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This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychol ogy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. The problems posed by metaphor and analogy are among the most challenging that confront the field of knowledge representation. In this study, Eileen Way has drawn upon the combined resources of philosophy, psychology, and computer science in developing a systematic and illuminating theoretical framework for understanding metaphors and analogies. While her work provides solutions to difficult problems of knowledge representation, it goes much further by investigating some of the most important philosophical assumptions that prevail within artificial intelligence today. By exposing the limitations inherent in the assumption that languages are both literal and truth-functional, she has advanced our grasp of the nature of language itself. J.R.F.

Advanced Design and Manufacturing Based on STEP

Author: Xun Xu
Publisher: Springer Science & Business Media
ISBN: 1848827393
Format: PDF, Docs
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Design and manufacturing is the essential element in any product development lifecycle. Industry vendors and users have been seeking a common language to be used for the entire product development lifecycle that can describe design, manufacturing and other data pertaining to the product. Many solutions were proposed, the most successful being the Stadndard for Exchange of Product model (STEP). STEP provides a mechanism that is capable of describing product data, independent from any particular system. The nature of this description makes it suitable not only for neutral file exchange, but also as a basis for implementing, sharing and archiving product databases. ISO 10303-AP203 is the first and perhaps the most successful AP developed to exchange design data between different CAD systems. Going from geometric data (as in AP203) to features (as in AP224) represents an important step towards having the right type of data in a STEP-based CAD/CAM system. Of particular significance is the publication of STEP-NC, as an extension of STEP to NC, utilising feature-based concepts for CNC machining purposes. The aim of this book is to provide a snapshot of the recent research outcomes and implementation cases in the field of design and manufacturing where STEP is used as the primary data representation protocol. The 20 chapters are contributed by authors from most of the top research teams in the world. These research teams are based in national research institutes, industries as well as universities.