Logical and Relational Learning

Author: Luc De Raedt

Publisher: Springer Science & Business Media

ISBN: 3540688560

Category: Computers

Page: 387

View: 8213

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This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning.

Foundations of Rule Learning

Author: Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač

Publisher: Springer Science & Business Media

ISBN: 3540751971

Category: Computers

Page: 334

View: 9223

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Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning. The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.

Perspectives on Ontology Learning

Author: J. Lehmann,J. Völker

Publisher: IOS Press

ISBN: 1614993793

Category: Computers

Page: 300

View: 1765

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Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning. Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the creation of simple taxonomical structures, as well as on problems specifically related to knowledge modeling and representation using the Web Ontology Language. Perspectives on Ontology Learning is designed for researchers in the field of semantic technologies and developers of knowledge-based applications. It covers various aspects of ontology learning including ontology quality, user interaction, scalability, knowledge acquisition from heterogeneous sources, as well as the integration with ontology engineering methodologies.

Inductive Logic Programming

21st International Conference, ILP 2011, Windsor Great Park, UK, July 31 -- August 3, 2011, Revised Selected Papers

Author: Stephen Muggleton,Alireza Tamaddoni-Nezhad,Francesca A. Lisi

Publisher: Springer

ISBN: 3642319513

Category: Computers

Page: 406

View: 9307

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This book constitutes the thoroughly refereed post-proceedings of the 21st International Conference on Inductive Logic Programming, ILP 2011, held in Windsor Great Park, UK, in July/August 2011. The 24 revised full papers were carefully reviewed and selected from 66 submissions. Also included are five extended abstracts and three invited talks. The papers represent the diversity and vitality in present ILP research including ILP theory, implementations, probabilistic ILP, biological applications, sub-group discovery, grammatical inference, relational kernels, learning of Petri nets, spatial learning, graph-based learning, and learning of action models.

Inductive Logic Programming

24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers

Author: Jesse Davis,Jan Ramon

Publisher: Springer

ISBN: 331923708X

Category: Mathematics

Page: 211

View: 4670

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This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Conference on Inductive Logic Programming, ILP 2014, held in Nancy, France, in September 2014. The 14 revised papers presented were carefully reviewed and selected from 41 submissions. The papers focus on topics such as the inducing of logic programs, learning from data represented with logic, multi-relational machine learning, learning from graphs, and applications of these techniques to important problems in fields like bioinformatics, medicine, and text mining.

Markov Logic

An Interface Layer for Artificial Intelligence

Author: Pedro Domingos,Daniel Lowd

Publisher: Morgan & Claypool Publishers

ISBN: 1598296922

Category: Computers

Page: 145

View: 2394

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Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system. Table of Contents: Introduction / Markov Logic / Inference / Learning / Extensions / Applications / Conclusion

Introduction to Statistical Relational Learning

Author: Lise Getoor

Publisher: MIT Press

ISBN: 0262072882

Category: Computers

Page: 586

View: 7710

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Advanced statistical modeling and knowledge representation techniques for a newly emerging area of machine learning and probabilistic reasoning; includes introductory material, tutorials for different proposed approaches, and applications.

Neural-Symbolic Learning Systems

Foundations and Applications

Author: Artur S. d'Avila Garcez,Krysia B. Broda,Dov M. Gabbay

Publisher: Springer Science & Business Media

ISBN: 1447102118

Category: Computers

Page: 271

View: 6641

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Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.

Graph Data Modeling for NoSQL and SQL

Visualize Structure and Meaning

Author: Thomas Frisendal

Publisher: Technics Publications

ISBN: 1634621239

Category: Computers

Page: 214

View: 3740

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Master a graph data modeling technique superior to traditional data modeling for both relational and NoSQL databases (graph, document, key-value, and column), leveraging cognitive psychology to improve big data designs. From Karen Lopez’s Foreword: In this book, Thomas Frisendal raises important questions about the continued usefulness of traditional data modeling notations and approaches: Are Entity Relationship Diagrams (ERDs) relevant to analytical data requirements? Are ERDs relevant in the new world of Big Data? Are ERDs still the best way to work with business users to understand their needs? Are Logical and Physical Data Models too closely coupled? Are we correct in using the same notations for communicating with business users and developers? Should we refine our existing notations and tools to meet these new needs, or should we start again from a blank page? What new notations and approaches will we need? How will we use those to build enterprise database systems? Frisendal takes us through the history of data modeling, enterprise data models and traditional modeling methods. He points out, quite contentiously, where he feels we have gone wrong and in a few places where we got it right. He then maps out the psychology of meaning and context, while identifying important issues about where data modeling may or may not fit in business modeling. The main subject of this work is a proposal for a new exploration-driven modeling approach and new modeling notations for business concept models, business solutions models, and physical data models with examples on how to leverage those for implementing into any target database or datastore. These new notations are based on a property graph approach to modeling data.

Cognitive Computing: Theory and Applications

Author: Vijay V Raghavan,Venkat N. Gudivada,Venu Govindaraju,C.R. Rao

Publisher: Elsevier

ISBN: 0444637516

Category: Mathematics

Page: 404

View: 4870

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Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber security, neural networks, data driven speech recognition, and analytical platforms to study the brain-computer interface. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowned experts in their respective areas

A Handbook for Teaching and Learning in Higher Education

Enhancing academic practice

Author: Heather Fry,Steve Ketteridge,Stephanie Marshall

Publisher: Routledge

ISBN: 1317650220

Category: Education

Page: 452

View: 9079

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This entirely new edition of a very successful book focuses on developing professional academic skills for supporting and supervising student learning and effective teaching. It is built on the premise that the roles of those who teach in higher education are complex and multi-faceted. A Handbook for Teaching and Learning in Higher Education is sensitive to the competing demands of teaching, research, scholarship, and academic management. The new edition reflects and responds to the rapidly changing context of higher education and to current understanding of how to best support student learning. Drawing together a large number of expert authors, it continues to feature extensive use of case studies that show how successful teachers have implemented these ideas. It includes key topics such as student engagement and motivation, internationalisation, employability, inclusive strategies for teaching, effective use of technology and issues relating to postgraduate students and student retention. Part 1 explores a number of aspects of the context of UK higher education that affect the education of students, looking at the drivers of institutional behaviours and how to achieve success as a university teacher. Part 2 examines learning, teaching and supervising in higher education and includes chapters on working with diversity, encouraging independent learning and learning gain. Part 3 considers approaches to teaching and learning in different disciplines, covering a full range including arts and humanities, social sciences, experimental sciences through to medicine and dentistry. Written to support the excellence in teaching and learning design required to bring about student learning of the highest quality, this will be essential reading for all new lecturers, particularly anyone taking an accredited course in teaching and learning in higher education, as well as those experienced lecturers who wish to improve their teaching practice. Those working in adult learning and educational development will also find the book to be a particularly useful resource. In addition it will appeal to staff who support learning and teaching in various other roles.

The Oxford Handbook of Thinking and Reasoning

Author: Keith J. Holyoak,Robert G. Morrison

Publisher: Oxford University Press

ISBN: 0199313792

Category: Psychology

Page: 864

View: 9781

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The Oxford Handbook of Thinking and Reasoning brings together the contributions of many of the leading researchers in thinking and reasoning to create the most comprehensive overview of research on thinking and reasoning that has ever been available.

Probabilistic Inductive Logic Programming

Author: Luc De Raedt,Paolo Frasconi,Kristian Kersting,Stephen H. Muggleton

Publisher: Springer

ISBN: 354078652X

Category: Computers

Page: 341

View: 3271

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This book provides an introduction to probabilistic inductive logic programming. It places emphasis on the methods based on logic programming principles and covers formalisms and systems, implementations and applications, as well as theory.

Derived Relational Responding Applications for Learners with Autism and Other Developmental Disabilities

A Progressive Guide to Change

Author: Ruth Anne Rehfeldt,Yvonne Barnes-Holmes

Publisher: New Harbinger Publications

ISBN: 1608826392

Category: Psychology

Page: 400

View: 1055

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Copublished with Context Press Derived Relational Responding offers a series of revolutionary intervention programs for applied work in human language and cognition targeted at students with autism and other developmental disabilities. It presents a program drawn from derived stimulus relations that you can use to help students of all ages acquire foundational and advanced verbal, social, and cognitive skills. The first part of Derived Relational Responding provides step-by-step instructions for helping students learn relationally, acquire rudimentary verbal operants, and develop other basic language skills. In the second section of this book, you'll find ways to enhance students' receptive and expressive repertoires by developing their ability to read, spell, construct sentences, and use grammar. Finally, you'll find out how to teach students to apply the skills they've learned to higher order cognitive and social functions, including perspective-taking, empathy, mathematical reasoning, intelligence, and creativity. This applied behavior analytic training approach will help students make many substantial and lasting gains in language and cognition not possible with traditional interventions.

Neural-Symbolic Cognitive Reasoning

Author: Artur S. D'Avila Garcez,Luís C. Lamb,Dov M. Gabbay

Publisher: Springer Science & Business Media

ISBN: 3540732454

Category: Computers

Page: 197

View: 5924

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This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.

Dynamic Fuzzy Machine Learning

Author: Fanzhang Li,Li Zhang,Zhao Zhang

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110520656

Category: Computers

Page: 337

View: 5302

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Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Philosophy of Technology and Engineering Sciences

Author: N.A

Publisher: Elsevier

ISBN: 9780080930749

Category: Philosophy

Page: 1472

View: 7327

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The Handbook Philosophy of Technology and Engineering Sciences addresses numerous issues in the emerging field of the philosophy of those sciences that are involved in the technological process of designing, developing and making of new technical artifacts and systems. These issues include the nature of design, of technological knowledge, and of technical artifacts, as well as the toolbox of engineers. Most of these have thus far not been analyzed in general philosophy of science, which has traditionally but inadequately regarded technology as mere applied science and focused on physics, biology, mathematics and the social sciences. • First comprehensive philosophical handbook on technology and the engineering sciences • Unparalleled in scope including explorative articles • In depth discussion of technical artifacts and their ontology • Provides extensive analysis of the nature of engineering design • Focuses in detail on the role of models in technology

Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications

Concepts and Applications

Author: Trajkovski, Goran

Publisher: IGI Global

ISBN: 1609601734

Category: Computers

Page: 396

View: 9609

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Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications discusses research on emerging technologies and systems based on agent and multi-agent paradigms across various fields of science, engineering and technology. This book is a collection of work that covers conceptual frameworks, case studies, and analysis while serving as a medium of communication among researchers from academia, industry and government.

The Quest for Artificial Intelligence

Author: Nils J. Nilsson

Publisher: Cambridge University Press

ISBN: 1139642820

Category: Computers

Page: N.A

View: 3174

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Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.

Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps

Author: W. B. Vasantha Kandasamy,Florentin Smarandache

Publisher: Infinite Study

ISBN: 1931233764

Category: Expert systems (Computer science)

Page: 211

View: 440

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In a world of chaotic alignments, traditional logic with its strict boundaries of truth and falsity has not imbued itself with the capability of reflecting the reality. Despite various attempts to reorient logic, there has remained an essential need for an alternative system that could infuse into itself a representation of the real world. Out of this need arose the system of Neutrosophy (the philosophy of neutralities, introduced by FLORENTIN SMARANDACHE), and its connected logic Neutrosophic Logic, which is a further generalization of the theory of Fuzzy Logic. In this book we study the concepts of Fuzzy Cognitive Maps (FCMs) and their Neutrosophic analogue, the Neutrosophic Cognitive Maps (NCMs). Fuzzy Cognitive Maps are fuzzy structures that strongly resemble neural networks, and they have powerful and far-reaching consequences as a mathematical tool for modeling complex systems. Neutrosophic Cognitive Maps are generalizations of FCMs, and their unique feature is the ability to handle indeterminacy in relations between two concepts thereby bringing greater sensitivity into the results. Some of the varied applications of FCMs and NCMs which has been explained by us, in this book, include: modeling of supervisory systems; design of hybrid models for complex systems; mobile robots and in intimate technology such as office plants; analysis of business performance assessment; formalism debate and legal rules; creating metabolic and regulatory network models; traffic and transportation problems; medical diagnostics; simulation of strategic planning process in intelligent systems; specific language impairment; web-mining inference application; child labor problem; industrial relations: between employer and employee, maximizing production and profit; decision support in intelligent intrusion detection system; hyper-knowledge representation in strategy formation; female infanticide; depression in terminally ill patients and finally, in the theory of community mobilization and women empowerment relative to the AIDS epidemic.