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Author: Collectif
Publisher: Hermann
ISBN: 9782705687335
Category :
Languages : fr
Pages : 216
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Book Description
La selection d'articles publies dans le present recueil constitue les actes de la 16e Conference Francophone Extraction et Gestion des Connaissances (EGC 2016) qui s'est deroulee a l'universite de Reims du 18 au 22 janvier 2016. L'objectif des conferences EGC est de rassembler des chercheurs de disciplines relevant de l'extraction et la gestion des connaissances (apprentissage automatique, ingenierie et representation des connaissances, statistique et analyse de donnees, fouille de donnees, systemes d'information, bases de donnees) et des specialistes du monde industriel et des entreprises qui deploient des methodes d'extraction et de gestion des connaissances sur des donnees reelles. Cette conference est un evenement majeur federateur de la communaute francophone en Extraction et Gestion des Connaissances et regroupe des chercheurs de nombreux pays (notamment France, Belgique, Suisse, Canada, Afrique du Nord). Le programme de la conference comprend aussi des presentations de chercheurs invites reconnus mondialement pour leurs travaux. Les communications rassemblees dans ce volume traduisent a la fois le caractere multidisciplinaire des travaux de recherche presentes, la richesse des applications sous-jacentes et la vitalite des innovations issues de l'extraction et de la gestion des connaissances.
Author: Collectif
Publisher: Hermann
ISBN: 9782705687335
Category :
Languages : fr
Pages : 216
Get Book Here
Book Description
La selection d'articles publies dans le present recueil constitue les actes de la 16e Conference Francophone Extraction et Gestion des Connaissances (EGC 2016) qui s'est deroulee a l'universite de Reims du 18 au 22 janvier 2016. L'objectif des conferences EGC est de rassembler des chercheurs de disciplines relevant de l'extraction et la gestion des connaissances (apprentissage automatique, ingenierie et representation des connaissances, statistique et analyse de donnees, fouille de donnees, systemes d'information, bases de donnees) et des specialistes du monde industriel et des entreprises qui deploient des methodes d'extraction et de gestion des connaissances sur des donnees reelles. Cette conference est un evenement majeur federateur de la communaute francophone en Extraction et Gestion des Connaissances et regroupe des chercheurs de nombreux pays (notamment France, Belgique, Suisse, Canada, Afrique du Nord). Le programme de la conference comprend aussi des presentations de chercheurs invites reconnus mondialement pour leurs travaux. Les communications rassemblees dans ce volume traduisent a la fois le caractere multidisciplinaire des travaux de recherche presentes, la richesse des applications sous-jacentes et la vitalite des innovations issues de l'extraction et de la gestion des connaissances.
Author: Edwin Diday
Publisher: John Wiley & Sons
ISBN: 1786305763
Category : Business & Economics
Languages : en
Pages : 258
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Book Description
Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction. Special kinds of data (symbolic, network, complex, compositional) are increasingly frequent in data science. These data require specific methodologies, but there is a lack of reference work in this field. Advances in Data Science fills this gap. It presents a collection of up-to-date contributions by eminent scholars following two international workshops held in Beijing and Paris. The 10 chapters are organized into four parts: Symbolic Data, Complex Data, Network Data and Clustering. They include fundamental contributions, as well as applications to several domains, including business and the social sciences.
Author: Henri Cohen
Publisher: Elsevier
ISBN: 0128097663
Category : Psychology
Languages : en
Pages : 1277
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Book Description
Handbook of Categorization in Cognitive Science, Second Edition presents the study of categories and the process of categorization as viewed through the lens of the founding disciplines of the cognitive sciences, and how the study of categorization has long been at the core of each of these disciplines. The literature on categorization reveals there is a plethora of definitions, theories, models and methods to apprehend this central object of study. The contributions in this handbook reflect this diversity. For example, the notion of category is not uniform across these contributions, and there are multiple definitions of the notion of concept. Furthermore, the study of category and categorization is approached differently within each discipline. For some authors, the categories themselves constitute the object of study, whereas for others, it is the process of categorization, and for others still, it is the technical manipulation of large chunks of information. Finally, yet another contrast has to do with the biological versus artificial nature of agents or categorizers. - Defines notions of category and categorization - Discusses the nature of categories: discrete, vague, or other - Explores the modality effects on categories - Bridges the category divide - calling attention to the bridges that have already been built, and avenues for further cross-fertilization between disciplines
Author: Yanio Hernández Heredia
Publisher: Springer
ISBN: 3030011321
Category : Computers
Languages : en
Pages : 391
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Book Description
This book constitutes the refereed proceedings of the 6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018, held in Havana, Cuba, in September 2018. The 42 full papers presented were carefully reviewed and selected from 101 submissions. The papers promote and disseminate ongoing research on mathematical methods and computing techniques for artificial intelligence and pattern recognition, in particular in bioinformatics, cognitive and humanoid vision, computer vision, image analysis and intelligent data analysis, as well as their application in a number of diverse areas such as industry, health, robotics, data mining, opinion mining and sentiment analysis, telecommunications, document analysis, and natural language processing and recognition.
Author: Roman Vershynin
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299
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Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Author: Kuize Zhang
Publisher: Springer
ISBN: 3030259722
Category : Technology & Engineering
Languages : en
Pages : 226
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Book Description
Discrete-Time and Discrete-Space Dynamical Systems provides a systematic characterization of the similarities and differences of several types of discrete-time and discrete-space dynamical systems, including: Boolean control networks; nondeterministic finite-transition systems; finite automata; labelled Petri nets; and cellular automata. The book's perspective is primarily based on topological properties though it also employs semitensor-product and graph-theoretic methods where appropriate. It presents a series of fundamental results: invertibility, observability, detectability, reversiblity, etc., with applications to systems biology. Academic researchers with backgrounds in applied mathematics, engineering or computer science and practising engineers working with discrete-time and discrete-space systems will find this book a helpful source of new understanding for this increasingly important class of systems. The basic results to be found within are of fundamental importance for further study of related problems such as automated synthesis and safety control in cyber-physical systems using formal methods.
Author: Sobczak-Michalowska, Marzena
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 315
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Book Description
The need for tailored data for machine learning models is often unsatisfied, as it is considered too much of a risk in the real-world context. Synthetic data, an algorithmically birthed counterpart to operational data, is the linchpin for overcoming constraints associated with sensitive or regulated information. In high-dimensional data, where the dimensions of features and variables often surpass the number of available observations, the emergence of synthetic data heralds a transformation. Applications of Synthetic High Dimensional Data delves into the algorithms and applications underpinning the creation of synthetic data, which surpass the capabilities of authentic datasets in many cases. Beyond mere mimicry, synthetic data takes center stage in prioritizing the mathematical domain, becoming the crucible for training robust machine learning models. It serves not only as a simulation but also as a theoretical entity, permitting the consideration of unforeseen variables and facilitating fundamental problem-solving. This book navigates the multifaceted advantages of synthetic data, illuminating its role in protecting the privacy and confidentiality of authentic data. It also underscores the controlled generation of synthetic data as a mechanism to safeguard private information while maintaining a controlled resemblance to real-world datasets. This controlled generation ensures the preservation of privacy and facilitates learning across datasets, which is crucial when dealing with incomplete, scarce, or biased data. Ideal for researchers, professors, practitioners, faculty members, students, and online readers, this book transcends theoretical discourse.
Author: Inès Saad
Publisher: Springer Nature
ISBN: 3030859770
Category : Computers
Languages : en
Pages : 190
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Book Description
This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021. The International Conference on Information and Knowledge Systems (ICIKS 2021) gathered both researchers and practitioners in the fields of Information Systems, Artificial Intelligence, Knowledge Management and Decision Support. ICIKS seeks to promote discussions on various organizational, technological, and socio-cultural aspects of research in the design and use of information and knowledge systems in organizations. The 10 full and 2 short papers presented in this volume were carefully reviewed and selected from 32 submissions. They were organized in topical sections as follows: knowledge systems and decision making; machine learning, recommender systems, and knowledge systems; and security, artificial intelligence, and information systems.
Author: Norman R. Swanson
Publisher: MDPI
ISBN: 303650852X
Category : Business & Economics
Languages : en
Pages : 196
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Book Description
Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.
Author: John Wright
Publisher: Cambridge University Press
ISBN: 1108805558
Category : Computers
Languages : en
Pages : 718
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Book Description
Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candès.
