Semantic Knowledge Representation For Information Retrieval
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Semantic Knowledge Representation For Information Retrieval
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Author : Winfried Gödert
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2014-08-19
Semantic Knowledge Representation For Information Retrieval written by Winfried Gödert and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-19 with Computers categories.
This book covers the basics of semantic web technologies and indexing languages, and describes their contribution to improve methods of formal knowledge representation and reasoning. The methodologies included combine the specifics of indexing languages, Web representation languages and intersystem relations, and explain their contribution to search functionalities in information retrieval scenarios. An example oriented discussion, considering aspects of conceptual and semantic interoperability in processes of subject querying and knowledge exploration is provided. The book is relevant to information scientists, knowledge workers and indexers. It provides a suitable combination of theoretical foundations and practical applications.
Representation Learning For Natural Language Processing
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Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2020-07-03
Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Computers categories.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
A Knowledge Representation Practionary
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Author : Michael K. Bergman
language : en
Publisher: Springer
Release Date : 2018-12-12
A Knowledge Representation Practionary written by Michael K. Bergman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Computers categories.
This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. This book follows Peirce's practical guidelines and universal categories in a structured approach to knowledge representation that captures differences in events, entities, relations, attributes, types, and concepts. Besides the ability to capture meaning and context, the Peircean approach is also well-suited to machine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy. Knowledge representation is shorthand for how to represent human symbolic information and knowledge to computers to solve complex questions. KR applications range from semantic technologies and knowledge management and machine learning to information integration, data interoperability, and natural language understanding. Knowledge representation is an essential foundation for knowledge-based AI. This book is structured into five parts. The first and last parts are bookends that first set the context and background and conclude with practical applications. The three main parts that are the meat of the approach first address the terminologies and grammar of knowledge representation, then building blocks for KR systems, and then design, build, test, and best practices in putting a system together. Throughout, the book refers to and leverages the open source KBpedia knowledge graph and its public knowledge bases, including Wikipedia and Wikidata. KBpedia is a ready baseline for users to bridge from and expand for their own domain needs and applications. It is built from the ground up to reflect Peircean principles. This book is one of timeless, practical guidelines for how to think about KR and to design knowledge management (KM) systems. The book is grounded bedrock for enterprise information and knowledge managers who are contemplating a new knowledge initiative. This book is an essential addition to theory and practice for KR and semantic technology and AI researchers and practitioners, who will benefit from Peirce's profound understanding of meaning and context.
Graph Based Knowledge Representation
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Author : Michel Chein
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-20
Graph Based Knowledge Representation written by Michel Chein and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-20 with Mathematics categories.
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.
Spinning The Semantic Web
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Author : Dieter Fensel
language : en
Publisher: MIT Press
Release Date : 2003
Spinning The Semantic Web written by Dieter Fensel and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
A guide to the Semantic Web, which will transform the Web into a structured network of resources organized by meaning and relationships.
Knowledge Representation In The Social Semantic Web
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Author : Katrin Weller
language : en
Publisher: Walter de Gruyter
Release Date : 2010-10-29
Knowledge Representation In The Social Semantic Web written by Katrin Weller and has been published by Walter de Gruyter this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-29 with Language Arts & Disciplines categories.
The main purpose of this book is to sum up the vital and highly topical research issue of knowledge representation on the Web and to discuss novel solutions by combining benefits of folksonomies and Web 2.0 approaches with ontologies and semantic technologies. The book contains an overview of knowledge representation approaches in past, present and future, introduction to ontologies, Web indexing and in first case the novel approaches of developing ontologies.
Legal Knowledge Representation Automatic Text Analysis In Public International And European Law
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Author : Erich Schweighofer
language : en
Publisher: Kluwer Law International B.V.
Release Date : 1999-10-19
Legal Knowledge Representation Automatic Text Analysis In Public International And European Law written by Erich Schweighofer and has been published by Kluwer Law International B.V. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-10-19 with Law categories.
This volume is a presentation of all methods of legal knowledge representation from the point of view of jurisprudence as well as computer science. A new method of automatic analysis of legal texts is presented in four case studies. Law is seen as an information system with legally formalised information processes. The achieved coverage of legal knowledge in information retrieval systems has to be followed by the next step: conceptual indexing and automatic analysis of texts. Existing approaches of automatic knowledge representations do not have a proper link to the legal language in information systems. The concept-based model for semi-automatic analysis of legal texts provides this necessary connection. The knowledge base of descriptors, context-sensitive rules and meta-rules formalises properly all important passages in the text corpora for automatic analysis. Statistics and self-organising maps give assistance in knowledge acquisition. The result of the analysis is organised with automatically generated hypertext links. Four case studies show the huge potential but also some drawbacks of this approach.
Concepts Ontologies And Knowledge Representation
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Author : Grega Jakus
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-22
Concepts Ontologies And Knowledge Representation written by Grega Jakus and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-22 with Computers categories.
Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to know the field of knowledge representation quickly, or would like to be up to date with current developments in the field. It is also useful for those dealing with implementation as examples of numerous operational systems are also given.
Semantic Ai In Knowledge Graphs
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Author : Sanju Tiwari
language : en
Publisher: CRC Press
Release Date : 2023-08-21
Semantic Ai In Knowledge Graphs written by Sanju Tiwari and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-21 with Computers categories.
Recent combinations of semantic technology and artificial intelligence (AI) present new techniques to build intelligent systems that identify more precise results. Semantic AI in Knowledge Graphs locates itself at the forefront of this novel development, uncovering the role of machine learning to extend the knowledge graphs by graph mapping or corpus-based ontology learning. Securing efficient results via the combination of symbolic AI and statistical AI such as entity extraction based on machine learning, text mining methods, semantic knowledge graphs, and related reasoning power, this book is the first of its kind to explore semantic AI and knowledge graphs. A range of topics are covered, from neuro-symbolic AI, explainable AI and deep learning to knowledge discovery and mining, and knowledge representation and reasoning. A trailblazing exploration of semantic AI in knowledge graphs, this book is a significant contribution to both researchers in the field of AI and data mining as well as beginner academicians.
Semantic Based Visual Information Retrieval
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Author : Zhang, Yu-Jin
language : en
Publisher: IGI Global
Release Date : 2006-11-30
Semantic Based Visual Information Retrieval written by Zhang, Yu-Jin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-30 with Computers categories.
"This book presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, human-computer interaction, and more"--Provided by publisher.