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During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.
The theory of belief functions, also known as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the Transferable Belief Model and the Theory of Hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories. This volume contains the proceedings of the 2nd International Conference on Belief Functions that was held in Compiègne, France on 9-11 May 2012. It gathers 51 contributions describing recent developments both on theoretical issues (including approximation methods, combination rules, continuous belief functions, graphical models and independence concepts) and applications in various areas including classification, image processing, statistics and intelligent vehicles.
Geometric properties and relations play central roles in the description and processing of spatial data. The properties and relations studied by mathematicians usually have precise definitions, but verbal descriptions often involve imprecisely defined concepts such as elongatedness or proximity. The methods used in soft computing provide a framework for formulating and manipulating such concepts. This volume contains eight papers on the soft definition and manipulation of spatial relations and gives a comprehensive summary on the subject.
Annotation. This book constitutes the refereed proceedings of the 5th International Symposium on Biomedical Simulation, ISBMS 2010, held in Phoenix, AZ, USA, in January 2010.The 19 revised full papers were carefully reviewed and selected from 41 submissions. The manuscripts are organized in four thematic sections covering some of the key aspects of biomedical simulation: soft tissue properties, modelling and segmentation, simulation of biophysical processes and real-time interactive simulation.
The aim of this handbook is to create, for the first time, a systematic account of the field of spatial logic. The book comprises a general introduction, followed by fourteen chapters by invited authors. Each chapter provides a self-contained overview of its topic, describing the principal results obtained to date, explaining the methods used to obtain them, and listing the most important open problems. Jointly, these contributions constitute a comprehensive survey of this rapidly expanding subject.
This book contains the refereed proceedings of the 13th International Symposium on Mathematical Morphology, ISMM 2017, held in Fontainebleau, France, in May 2017. The 36 revised full papers presented together with 4 short papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on algebraic theory, max-plus and max-min mathematics; discrete geometry and discrete topology; watershed and graph-based segmentation; trees and hierarchies; topological and graph-based clustering, classification and filtering; connected operators and attribute filters; PDE-based morphology; scale-space representations and nonlinear decompositions; computational morphology; object detection; and biomedical, material science and physical applications.
The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably complex geometric space, and manipulated in that space, for example, combined or conditioned. In the chapters in Part I, Theories of Uncertainty, the author offers an extensive recapitulation of the state of the art in the mathematics of uncertainty. This part of the book contains the most comprehensive summary to date of the whole of belief theory, with Chap. 4 outlining for the first time, and in a logical order, all the steps of the reasoning chain assoc...
This book contains the refereed proceedings of the 11th International Symposium on Mathematical Morphology, ISMM 2013 held in Uppsala, Sweden, in May 2013. The 41 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 52 submissions. The papers are organized in topical sections on theory; trees and hierarchies; adaptive morphology; colour; manifolds and metrics; filtering; detectors and descriptors; and applications.
This book constitutes the refereed proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2009, held in Verona, Italy, July 1-3, 2009. There are 76 revised full papers presented together with 3 invited lectures by three outstanding researchers in the area. All papers were carefully reviewed and selected from 118 submissions for inclusion in the book. The papers are organized in topical sections on algorithms for uncertain inference, argumentation systems, Bayesian networks, Belief functions, Belief revision and inconsistency handling, classification and clustering, conditioning, independence, inference, default reasoning, foundations of reasoning, decision making under uncertainty, Fuzzy sets and Fuzzy logic, implementation and application of uncertain systems, logics for reasoning under uncertainty, Markov decision process, and Mathematical Fuzzy Logic.