Foundations of Large-Scale Multimedia Information Management and Retrieval


Book Description

"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions. The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval. Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.




Big Data Analytics for Large-Scale Multimedia Search


Book Description

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.




Multimedia Information Retrieval


Book Description

Novel processing and searching tools for the management of new multimedia documents have developed. Multimedia Information Retrieval (MIR) is an organic system made up of Text Retrieval (TR); Visual Retrieval (VR); Video Retrieval (VDR); and Audio Retrieval (AR) systems. So that each type of digital document may be analysed and searched by the elements of language appropriate to its nature, search criteria must be extended. Such an approach is known as the Content Based Information Retrieval (CBIR), and is the core of MIR. This novel content-based concept of information handling needs to be integrated with more traditional semantics. Multimedia Information Retrieval focuses on the tools of processing and searching applicable to the content-based management of new multimedia documents. Translated from Italian by Giles Smith, the book is divided into two parts. Part one discusses MIR and related theories, and puts forward new methodologies; part two reviews various experimental and operating MIR systems, and presents technical and practical conclusions. - Gives a complete, organic picture of MIR and CBIR - Proposes a novel conceptualisation around the ideas of Information Retrieval (IR) and digital document management in the context of Library and Information Science (LIS) - Relevant for both library and information science and information technology specialists







Information Modelling and Knowledge Bases XXVII


Book Description

Information modeling has become an increasingly important topic for researchers, designers and users of information systems. In the course of the last three decades, information modeling and knowledge bases have become essential, not only with regard to information systems and computer science in an academic context, but also with the use of information technology for business purposes. This book presents 29 papers selected and upgraded from those delivered at the 25th International Conference on Information Modelling and Knowledge Bases (EJC 2015), held in Maribor, Slovenia, in June 2015. The aim of the conference is to bring together experts from different areas of computer science and other disciplines, including philosophy and logic, cognitive science, knowledge management, linguistics, and management science, with a view to understanding and solving problems and applying research results to practice. Areas covered by the papers include: conceptual modeling; knowledge and information modeling and discovery; linguistic modeling; cross-cultural communication and social computing; environmental modeling and engineering; and multimedia data modeling and systems. The book will be of interest to all those whose work involves the development or use of information modeling and knowledge bases.




Introduction to Information Retrieval


Book Description

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.










Cyber Security Intelligence and Analytics


Book Description

This book presents the outcomes of the 2019 International Conference on Cyber Security Intelligence and Analytics (CSIA2019), an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly focusing on threat intelligence, analytics, and countering cyber crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods and applications on all aspects of Cyber Security Intelligence and Analytics.




Multimedia Database Systems


Book Description

Multimedia Database Systems: Design and Implementation Strategies is a compendium of the state-of-the-art research and development work pertaining to the problems and issues in the design and development of multimedia database systems. The chapters in the book are developed from presentations given at previous meetings of the International Workshop on Multi-Media Data Base Management Systems (IW-MMDBMS), and address the following issues: development of adequate multimedia database models, design of multimedia database query and retrieval languages, design of indexing and organization techniques, development of efficient and reliable storage models, development of efficient and dependable retrieval and delivery strategies, and development of flexible, adaptive, and reliable presentation techniques.