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Multimedia Data Mining and Knowledge Discovery
Multimedia Data Mining and Knowledge Discovery provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research. Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications.
Multimedia big data computing for IoT applications : Concepts, paradigms and solutions
This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms.
Data mining and knowledge management ; Chinese academy of sciences symposium CASDMKD 2004, Beijing, China, July 12-14, 2004, Revised Paper
Knowledge management for enterprise: These papers address various issues related to the application of knowledge management in corporations using various techniques. A particular emphasis here is on coordination and cooperation. • Risk management: Better knowledge management also requires more advanced techniques for risk management, to identify, control, and minimize the impact of uncertain events, as shown in these papers, using fuzzy set theory and other approaches for better risk management. • Integration of data mining and knowledge management: As indicated earlier, the integration of these two research fields is still in the early stage. Nevertheless, as shown in the papers selected in this volume, researchers have endearored to integrate data mining methods such as neural networks with various aspects related to knowledge management,
Advances in Visual Information Systems ; 9th International Conference, VISUAL 2007 Shanghai, China, June 28-29, 2007 Revised Selected Papers
The visual information systems paradigm continues to evolve, and the unrelenting exponential growth in the amount of digital visual data underlines the escalating importance of how such data are effectively managed and deployed.It covered image and video retrieval, visual biometrics, intelligent visual information processing, visual data mining, ubiquitous and mobile visual information systems, visual semantics, 2D/3D graphical visual data retrieval and applications of visual information systems.
