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Knowledge Integration Methods for Probabilistic Knowledge-based Systems

Knowledge Integration Methods for Probabilistic Knowledge-based Systems PDF Author: Van Tham Nguyen
Publisher: CRC Press
ISBN: 100080996X
Category : Business & Economics
Languages : en
Pages : 203

Book Description
Knowledge-based systems and solving knowledge integrating problems have seen a great surge of research activity in recent years. Knowledge Integration Methods provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases. The book also provides the mathematical background to solving problems of restoring consistency and integrating probabilistic knowledge bases in the integrating process. The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more. This text will be useful for computer science graduates and PhD students, in addition to researchers and readers working on knowledge management and ontology interpretation.

Knowledge Integration Methods for Probabilistic Knowledge-based Systems

Knowledge Integration Methods for Probabilistic Knowledge-based Systems PDF Author: Van Tham Nguyen
Publisher: CRC Press
ISBN: 100080996X
Category : Business & Economics
Languages : en
Pages : 203

Book Description
Knowledge-based systems and solving knowledge integrating problems have seen a great surge of research activity in recent years. Knowledge Integration Methods provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases. The book also provides the mathematical background to solving problems of restoring consistency and integrating probabilistic knowledge bases in the integrating process. The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more. This text will be useful for computer science graduates and PhD students, in addition to researchers and readers working on knowledge management and ontology interpretation.

Probabilistic Graphical Models

Probabilistic Graphical Models PDF Author: Linda C. van der Gaag
Publisher: Springer
ISBN: 3319114336
Category : Computers
Languages : en
Pages : 609

Book Description
This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning.

Computational Collective Intelligence

Computational Collective Intelligence PDF Author: Ngoc Thanh Nguyen
Publisher: Springer
ISBN: 3319984438
Category : Computers
Languages : en
Pages : 578

Book Description
This two-volume set (LNAI 11055 and LNAI 11056) constitutes the refereed proceedings of the 10th International Conference on Collective Intelligence, ICCCI 2018, held in Bristol, UK, in September 2018 The 98 full papers presented were carefully reviewed and selected from 240 submissions. The conference focuses on knowledge engineering and semantic web, social network analysis, recommendation methods and recommender systems, agents and multi-agent systems, text processing and information retrieval, data mining methods and applications, decision support and control systems, sensor networks and internet of things, as well as computer vision techniques.

Probabilistic Methods in Expert Systems

Probabilistic Methods in Expert Systems PDF Author: Romano Scozzafava
Publisher:
ISBN:
Category : Expert systems (Computer science)
Languages : en
Pages : 218

Book Description


Artificial Intelligence Abstracts

Artificial Intelligence Abstracts PDF Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 448

Book Description


Advanced Topics in Artificial Intelligence

Advanced Topics in Artificial Intelligence PDF Author: Vladimír Mařík
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 504

Book Description
"This volume contains the texts of 26 lectures and contributions to the program of the International Summer School on Advanced Topics in Artificial Intelligence held in Prague, Czechoslovakia, July 6-17, 1992. The summerschool was intended for (postgraduate) students, researchers and all those who want to learn about recent progress in both theoretical and applied AI. The papers in the volume are organized into nine parts: - Introduction - Logic and logic programming - Machine learning - Planning and scheduling - Uncertainty - Second generation expert systemsand knowledge engineering - Qualitative reasoning - Neurocomputing -Natural language and interfaces"--PUBLISHER'S WEBSITE.

Proceedings of the ... International IEEE Conference on Tools for Artificial Intelligence

Proceedings of the ... International IEEE Conference on Tools for Artificial Intelligence PDF Author:
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 402

Book Description


The Vision of Ames Research Center

The Vision of Ames Research Center PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 148

Book Description


Library & Information Science Abstracts

Library & Information Science Abstracts PDF Author:
Publisher:
ISBN:
Category : Information science
Languages : en
Pages : 922

Book Description


Knowledge Graphs and Big Data Processing

Knowledge Graphs and Big Data Processing PDF Author: Valentina Janev
Publisher: Springer Nature
ISBN: 3030531996
Category : Computers
Languages : en
Pages : 212

Book Description
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.