• Book

    Proceedings of 2021 Chinese Intelligent Systems Conference

    Auteur: Yingmin Jia et al.

    Proceedings of 2021 Chinese Intelligent Systems Conference

    • Auteur: Yingmin Jia et al.
    • ISBN: 978-981-16-6328-4

    This book presents the proceedings of the 17th Chinese Intelligent Systems Conference, held in Fuzhou, China, on Oct 16-17, 2021. It focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth study on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. The book is particularly suited for readers who are interested in learning intelligent system and control and artificial intelligence. The book can benefit researchers, engineers, and graduate students.

  • Book

    Data Classification and Incremental Clustering in Data Mining and Machine Learning

    Auteur: Sanjay Chakraborty, Sk Hafizul Islam, Debabrata Samanta

    Data Classification and Incremental Clustering in Data Mining and Machine Learning

    • Auteur: Sanjay Chakraborty, Sk Hafizul Islam, Debabrata Samanta
    • ISBN: 978-3-030-93088-2

    This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.

  • Book

    UML2. Pratique de la modélisation

    Auteur: Benoît Charroux, Aomar Osmani et Yann Thierry-Mieg

    UML2. Pratique de la modélisation

    • Auteur: Benoît Charroux, Aomar Osmani et Yann Thierry-Mieg
    • ISBN: 978-2-7440-4050-4

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  • Book

    Infrastructures de données spatiales

    Auteur: Hélène Rey-Valette, Chady Jabbour, Pierre Maurel, Jean-Michel Salles

    Infrastructures de données spatiales

    • Auteur: Hélène Rey-Valette, Chady Jabbour, Pierre Maurel, Jean-Michel Salles
    • ISBN: 978-2-7592-3515-5

    Les demandes et les usages des données spatiales satellitaires se développent et se diversifient de façon importante, en lien avec la précision, la fréquence des prises de vue et la taille des images. Ainsi, il convient de comprendre et de rendre compte des impacts de cette production croissante sur l'organisation et la rationalisation des structures qui les utilisent, mais aussi sur l'efficacité et la transparence des politiques publiques mobilisant ces informations. Les infrastructures de données spatiales (IDS) représentent des dispositifs essentiels : elles facilitent l'accès aux images (acquisition, traitement, archivage), ainsi que les processus de mutualisation et d'innovations méthodologiques. Elles constituent des biens publics informationnels et mobilisent des moyens croissants qui nécessitent de questionner les types de "modèles économiques" dont elles relèvent. Ce guide, pédagogique et opérationnel, s'adresse à l'ensemble des acteurs liés à la production ou à l'usage des informations spatiales. Il permet une lecture à la carte en fonction des centres d'intérêt et des disciplines, à travers de multiples encadrés et exemples. Il présente les concepts et les méthodes d'évaluation économique appliqués à l'information spatiale, en détaillant trois types d'approches selon que l'on veut estimer la valeur de l'information spatiale, mesurer les retombées économiques d'une IDS ou caractériser ses impacts par des approches multicritères.

  • Book

    Data mining and medical knowledge management: cases and applications

    Auteur: Petr Berka, Jan Rauch, Djamel Abdelkader Zighed, Petr Berka, Jan Rauch, Djamel Abdelkader Zighed

    Data mining and medical knowledge management: cases and applications

    • Auteur: Petr Berka, Jan Rauch, Djamel Abdelkader Zighed, Petr Berka, Jan Rauch, Djamel Abdelkader Zighed
    • ISBN: 978-1-60566-218-3

    The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.

  • Book

    Data Mining and Machine Learning: Fundamental Concepts and Algorithms

    Auteur: Mohammed J. Zaki, Wagner Meira Jr

    Data Mining and Machine Learning: Fundamental Concepts and Algorithms

    • Auteur: Mohammed J. Zaki, Wagner Meira Jr
    • ISBN: 978-1-108-47398-9

    The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.

  • Book

    Advanced Data Mining and Application

    Auteur: Gao Cong, Wei Emma Zhang, Wen-Chih Peng, Chengliang Li, Aixin Sun

    Advanced Data Mining and Application

    • Auteur: Gao Cong, Wei Emma Zhang, Wen-Chih Peng, Chengliang Li, Aixin Sun
    • ISBN: 978-3-319-69179-4

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  • Book

    Spatial Data Mining Theory and Application

    Auteur: Deren Li, Shuliang Wang, Deyi Li

    Spatial Data Mining Theory and Application

    • Auteur: Deren Li, Shuliang Wang, Deyi Li
    • ISBN: 978-3-662-48538-5

    This book is an updated version of a well-received book previously published in Chinese by Science Press of China (the first edition in 2006 and the second in 2013). It offers a systematic and practical overview of spatial data mining, which combines computer science and geo-spatial information science, allowing each field to profit from the knowledge and techniques of the other. To address the spatiotemporal specialties of spatial data, the authors introduce the key concepts and algorithms of the data field, cloud model, mining view, and Deren Li methods. The data field method captures the interactions between spatial objects by diffusing the data contribution from a universe of samples to a universe of population, thereby bridging the gap between the data model and the recognition model. The cloud model is a qualitative method that utilizes quantitative numerical characters to bridge the gap between pure data and linguistic concepts. The mining view method discriminates the different requirements by using scale, hierarchy, and granularity in order to uncover the anisotropy of spatial data mining. The Deren Li method performs data preprocessing to prepare it for further knowledge discovery by selecting a weight for iteration in order to clean the observed spatial data as much as possible. In addition to the essential algorithms and techniques, the book provides application examples of spatial data mining in geographic information science and remote sensing. The practical projects include spatiotemporal video data mining for protecting public security, serial image mining on nighttime lights for assessing the severity of the Syrian Crisis, and the applications in the government project ‘the Belt and Road Initiatives’.

  • Book

    Individual and Collective GraphMining Principles, Algorithms, and Applications

    Auteur: Danai Koutra, Christos Faloutsos

    Individual and Collective GraphMining Principles, Algorithms, and Applications

    • Auteur: Danai Koutra, Christos Faloutsos
    • ISBN: 9781681730400

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  • Book

    Principles of Data Mining

    Auteur: Max Bramer

    Principles of Data Mining

    • Auteur: Max Bramer
    • ISBN: 978-1-4471-7307-6

    This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.

  • Book

    Encyclopedia of Machine Learning and Data Mining

    Auteur: Claude Sammut, Geoffrey I. Webb

    Encyclopedia of Machine Learning and Data Mining

    • Auteur: Claude Sammut, Geoffrey I. Webb
    • ISBN: 978-1-4899-7502-7

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  • Book

    Advances in Research Methods for Information Systems Research: Data Mining, Data Envelopment Analysis, Value Focused Thinking

    Auteur: Kweku-Muata Osei-Bryson, Ojelanki Ngwenyama

    Advances in Research Methods for Information Systems Research: Data Mining, Data Envelopment Analysis, Value Focused Thinking

    • Auteur: Kweku-Muata Osei-Bryson, Ojelanki Ngwenyama
    • ISBN: 978-1-4614-9462-1, 978-1-4614-9463-8

    Advances in social science research methodologies and data analytic methods are changing the way research in information systems is conducted. New developments in statistical software technologies for data mining (DM) such as regression splines or decision tree induction can be used to assist researchers in systematic post-positivist theory testing and development. Established management science techniques like data envelopment analysis (DEA), and value focused thinking (VFT) can be used in combination with traditional statistical analysis and data mining techniques to more effectively explore behavioral questions in information systems research. As adoption and use of these research methods expand, there is growing need for a resource book to assist doctoral students and advanced researchers in understanding their potential to contribute to a broad range of research problems. Advances in Research Methods for Information Systems Research: Data Mining, Data Envelopment Analysis, Value Focused Thinking focuses on bridging and unifying these three different methodologies in order to bring them together in a unified volume for the information systems community. This book serves as a resource that provides overviews on each method, as well as applications on how they can be employed to address IS research problems. Its goal is to help researchers in their continuous efforts to set the pace for having an appropriate interplay between behavioral research and design science.