تحسين النتائح
ترتيب حسب
من
الى
الصفحة 3
الصفحة 3
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.
Law and the Semantic Web : Legal Ontologies, Methodologies, Legal Information Retrieval, and Applications
As part of this objective, ICT (information and communication technologies) services should become available for every citizen, and for all schools, homes and businesses. The book you have in front of you is about Semantic Web technology and law. Law is something omnipresent; all citizens — at some points in their lives — have to deal with it. In addition, law involves a large group of professionals, and is a mul- billion business world wide. Information technology is important because it that can improve citizens’ interaction with law, as well as improve legal professionals’ work environment. Legal professionals dedicate a significant amount of their time to finding, reading, analyzing and synthesizing information in order to take decisions, and prepare advice and trials, among other tasks. As part of the “Semantic-Based Knowledge and Content Systems” Strategic Objective, the European Commission is funding projects to construct technology to make the Semantic Web vision come true. 1 The articles in this book are related to two current foci of the Strategic Objective : • Knowledge acquisition and modelling, capturing knowledge from raw information and multimedia content in webs and other distributed repositories to turn poorly structured information into machi- processable knowledge.
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.
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.
Biological and medical data analysis ; Vol. 3745 ; 6th International symposium, ISBMDA 2005, Aveiro, Portugal, November 10-11, 2005, Proceedings
The 6th International Symposium on Biological and Medical Data Analysisaimed to become a place where researchersinvolved in these diverse but increas-ingly complementary areas could meet topresent and discuss their scientificresults.The papers in this volume discuss issues from statistical models to archi-tectures and applications to bioinformatics and biomedicine. They cover bothpractical experience and novel research ideas and concepts.
Biological and artificial intelligence environments
The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.
Bioinformatics technologies
Solving modern biological problems requires advanced computational methods. Bioinformatics evolved from the active interaction of two fast-developing disciplines, biology and information technology. The central issue of this emerging field is the transformation of often distributed and unstructured biological data into meaningful information. This book describes the application of well-established concepts and techniques from areas like data mining, machine learning, database technologies, and visualization techniques to problems like protein data analysis, genome analysis and sequence databases. Chen has collected contributions from leading researchers in each area. The chapters can be read independently, as each offers a complete overview of its specific area, or, combined, this monograph is a comprehensive treatment that will appeal to students, researchers, and R&D professionals in industry who need a state-of-the-art introduction into this challenging and exciting young field.
Bioinformatics research and development ; 2nd International Conference, BIRD 2008 Vienna, Austria, July 7-9, 2008 Proceedings
This book constitutes the refereed proceedings of the Second International Bioinformatics Research and Development Conference, BIRD 2008, held in Vienna, Austria in July 2008.
Bioinformatics : Problem Solving Paradigms
This book highlights basic paradigms of problem analysis and algorithm design in the context of core bioinformatics problems. Mathematically demanding themes are put across to the reader by properly chosen representations with the aid of lots of illustrations.
Bioinformatics
In this textbook present mathematical models in bioinformatics and they describe the biological problems that inspire the computer science tools used to handle the enormous data sets involved. The first part of the book covers the mathematical and computational methods, while the practical applications are presented in the second part. The mathematical presentation is descriptive and avoids unnecessary formalism, and yet remains clear and precise. Emphasis is laid on motivation through biological problems and cross applications. Each of the four chapters in the first part is accompanied by exercises and problems to support an understanding of the techniques presented. Each of the six chapters of the second part is devoted to some specific application domain: sequence alignment, molecular phylogenetics and coalescence theory, genomics, proteomics, RNA, and DNA microarrays. Each chapter concludes with a problems and projects section, to deepen the reader's understanding and to allow for the design of derived methods. Many of the projects involve publicly available software and/or Web-based bioinformatics depositories. Finally, the book closes with a thorough bibliography, reaching from classic research results to very recent findings, providing many pointers for future research.Overall, this volume is ideally suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on its mathematical and computer science background.
Assistive technologies, robotics, and automated machines in the health domain
The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.
Artificial intelligence in medicine
Provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting.
Applications of artificial intelligence, big data and internet of things in sustainable development
Focuses on different algorithms and models related to AI, big data and IoT used for various domains. It enables the reader to have a broader and deeper understanding of several perspectives regarding the dynamics, challenges, and opportunities for sustainable development using artificial intelligence, big data and IoT. Applications of Artificial Intelligence, Big Data and Internet of Things (IoT) in Sustainable Development focuses on IT-based advancements in multidisciplinary fields such as healthcare, finance, bioinformatics, industrial automation, and environmental science.
Anatomy ontologies for bioinformatics : Principles and practice
This book provides a timely and first-of-its-kind collection of contributed chapters on anatomy ontologies. It is interdisciplinary in its approach, bringing together relevant expertise from computing and biomedical studies, and covering both theoretical and applied aspects, with an emphasis on newer work relevant to the emerging Semantic Web.
Algorithms in Bioinformatics ; 8th International Workshop, WABI 2008, Karlsruhe, Germany, September 15-19, 2008. Proceedings
This book constitutes the refereed proceedings of the 8th International Workshop on Algorithms in Bioinformatics, WABI 2008, held in Karlsruhe, Germany, in September 2008 as part of the ALGO 2008 meeting.
Algorithms in Bioinformatics : Theory and Implementation
Explores a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields. Delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. Readers will also benefit from the inclusion of: A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast ; A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations ; Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices ; A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields ; An examination of information and entropy, including sequence logos and explanations related to their meaning ; A chapter on philosophical transactions that allows the reader a broader view of the prediction process ; Extensive worked examples with detailed case studies that point out the meaning of different results
Algorithmic Aspects of Bioinformatics
Advances in bioinformatics and systems biology require improved computational methods for analyzing data, while progress in molecular biology is in turn influencing the development of computer science methods. This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. This book describes topics in detail and presents formal models in a mathematically precise, yet intuitive manner, with many figures and chapter summaries, detailed derivations, and examples. It is well suited as an introduction into the field of bioinformatics, and will benefit students and lecturers in bioinformatics and algorithmics, while also offering practitioners an update on current research topics.
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
Advanced mathematical science for mobility society
The automotive industry has made steady progress in technological innovations under the names of Connected Autonomous-Shared-Electric (CASE) and Mobility as a Service (MaaS). Needless to say, mathematics and informatics are important to support such innovations. As the concept of cars and movement itself is diversifying, they are indispensable for grasping the essence of the future mobility society and building the foundation for the next generation. This book contains three main contents. 1. Mathematical models of flow 2. Mathematical methodsfor huge data and network analysis 3. Algorithm for mobility society The first one discusses mathematical models of pedestrian and traffic flow, as they are important for preventing accidents and achieving efficient transportation.
Managing Agile Business Technology : The Business and Technology Relationship Model in Practice
Describes in detail how the BTRM, combined with a focus on value creation and value delivery, will enable continuous change, in the context of current, emerging and future technologies. It illustrates the potential for real-time insight and control not previously considered and provides a wide range of information to plan an implementation, understand where AI can be applied, and its importance in the world of self-managing systems.
