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Logical and Relational Learning

This textbook covers logical and relational learning in depth, and hence provides an introduction to inductive logic programming (ILP), multirelational data mining (MRDM) and (statistical) relational learning (SRL). These subfields of data mining and machine learning are concerned with the analysis of complex and structured data sets that arise in numerous applications, such as bio- and chemoinformatics, network analysis, Web mining, natural language processing, within the rich representations offered by relational databases and computational logic.

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Logic Programming with Prolog

Logic Programming is the name given to a distinctive style of programming, very different from that of conventional programming languages such as C++ and Java. By far the most widely used Logic Programming language is Prolog. Prolog is a good choice for developing complex applications, especially in the field of Artificial Intelligence. This book does not assume that the reader is an experienced programmer or has a background in Mathematics, Logic or Artificial Intelligence. It starts from scratch and aims to arrive at the point where quite powerful programs can be written in the language. It is intended both as a textbook for an introductory course and as a self-study book. On completion the reader will know enough to use Prolog in their own research or practical projects. Each chapter has self-assessment exercises so that the reader may check their own progress. A glossary of the technical terms used completes the book.

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Location, Transport and Land-Use : Modelling Spatial-Temporal Information

Shows the use of statistical tools for forecasting and analyzing implications of land-use decisions. The idea is that la- use on a map is necessarily a consequence of individual, and often conflicting, siting decisions over time.

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Literature-based Discovery

When Don Swanson hypothesized a connection between Raynaud’s phenomenon and dietary fish oil, the field of literature-based discovery (LBD) was born. During the subsequent two decades a steady stream of researchers have published articles about LBD and the field has made steady progress in laying foundations and creating an identity. LBD is an inherently multi-disciplinary enterprise where collaborations between the information and biomedical sciences are readily encountered. It is the hope and intention that this volume will plant a flag in the ground and inspire new researchers to the LBD challenge.

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Linguistics for the age of AI

One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning—the deep, context-sensitive meaning that a person derives from spoken or written language.

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Linear Systems, Signal Processing and Hypercomplex Analysis ; Chapman University, November 2017

includes contributions originating from a conference held at Chapman University during November 14-19, 2017. It presents original research by experts in signal processing, linear systems, operator theory, complex and hypercomplex analysis and related topics.

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Learning from data streams : Processing techniques in sensor networks

The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education.

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Learn to Tango with D

Learn to Tango with D introduces you to the powerful D language, with special attention given to the Tango software library. A concise yet thorough overview of the language's syntax and features is presented, followed by an introduction to Tango, the popular general–purpose library you'll find invaluable when building your D applications.

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Knowledge Sharing in the Integrated Enterprise : Interoperability Strategies for the Enterprise Architect

The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.

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Knowledge Representation and the Semantics of Natural Language

This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.

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Knowledge Processing with Interval and Soft Computing

In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++.

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Knowledge graphs and big data processing

This 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.

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Java Challenges 100+ : Proven Tasks that Will Prepare You for Anything

Expand your knowledge of Java with this entertaining learning guide, which features 100+ exercises and programming challenges. Java Challenges will prepare you for your next exam or job interview, and covers many practical topics, such as strings, arrays, data structures, recursion, and date and time. The APIs and other material included in this book are Java 17 compatible. You will: Improve your Java knowledge by solving enjoyable but challenging programming puzzles / Solve mathematical problems, recursions, strings, arrays and more / Manage data processing and data structures like lists, sets, maps / Handle advanced recursion as well as binary trees, sorting and searching / Gamify key fundamentals for fun and easier reinforcement

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Computational analysis and deep learning for medical care : Principles, methods, and applications

Focuses on the sophisticated methods for improving dye extraction and dyeing properties which will minimize the use of bioresource products. This book also brings out the innovative ways of wet chemical processing to alleviate the environmental impacts arising from this sector.

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Computable Models of the Law : Languages, Dialogues, Games, Ontologies

This book originate from a workshop held at the European University Institute of Florence, Italy, in December 2006. The workshop was devoted to the discussion of the different ways of understanding and explaining contemporary law, for the purpose of building computable models of it -- especially models enabling the development of computer applications for the legal domain.

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Complexity of Constraints : An Overview of Current Research Themes

This state-of-the-art survey contains the papers that were invited by the organizers after conclusion of an International Dagstuhl-Seminar on Complexity of Constraints, held in Dagstuhl Castle, Germany, in October 2006.

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Classification and Modeling with Linguistic Information Granules : Advanced Approaches to Linguistic Data Mining

Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod­ els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe­ matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com­ puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter­ net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and modeling, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

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Charting a new course : Natural language processing and information retrieval : Essays in Honour of Karen Spärck Jones

This book celebrates the life and work of Karen Spärck Jones in her seventieth year. she is one of the major figures of 20th century and early 21st Century computing and information processing. It book consists of fifteen new and original chapters written by leading international authorities reviewing the state of the art and her influence in the areas in which Karen Spärck Jones has been active. Although she has a publication record which goes back over forty years, it is clear even the very early work reviewed in the book can be read with profit by those working on recent developments in information processing like bioinformatics and the semantic web.

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Body Sensor Networks

While the problems of long-term stability and biocompatibility are being addressed, several promising prototypes are starting to emerge for managing patients with acute diabetes, for treatment of epilepsy and other debilitating neurological disorders and for monitoring of patients with chronic cardiac diseases. Despite the technological developments in sensing and monitoring devices, issues related to system integration, sensor miniaturization, low-power sensor interface circuitry design, wireless telemetric links and signal processing still have to be investigated.

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Biomedical data mining for information retrieval : Methodologies, techniques, and applications

Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.

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