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With a variety of media types, multimedia data engineering has emerged as a new opportunity to create techniques and tools that empower the development of the next generation of multimedia databases and information systems. Multimedia Data Engineering Applications and Processing presents different aspects of multimedia data engineering and management research. This collection of recent theories, technologies and algorithms brings together a detailed understanding of multimedia engineering and its applications. This reference source will be of essential use for researchers, scientists, professionals and software engineers in the field of multimedia.
Multimedia and its rich semantics are profligate in today’s digital environment. Databases and content management systems serve as essential tools to ensure that the endless supply of multimedia content are indexed and remain accessible to end users. Methods and Innovations for Multimedia Database Content Management highlights original research on new theories, algorithms, technologies, system design, and implementation in multimedia data engineering and management with an emphasis on automatic indexing, tagging, high-order ranking, and rule mining. This book is an ideal resource for university researchers, scientists, industry professionals, software engineers and graduate students.
Recent advances in computing, networking, storage, and information technology have enabled the collection and distribution of vast amounts of multimedia data in a variety of applications such as entertainment, education, environmental protection, e-commerce, public safety, digital government, homeland security, and manufacturing. The proliferation of multimedia data and its rich semantics have created the needs for advanced techniques for in-depth content processing, analysis, indexing, learning, mining, searching, management, and retrieval. The International Journal of Multimedia Data Engineering and Management (IJMDEM) addresses the corresponding issues and challenges and publishes original research on new theories, algorithms, technologies, system design, and implementation in multimedia data engineering and management.
»Digital Culture & Society« is a refereed, international journal, fostering discussion about the ways in which digital technologies, platforms and applications reconfigure daily lives and practices. It offers a forum for critical analysis and inquiries into digital media theory and provides a publication environment for interdisciplinary research approaches, contemporary theory developments and methodological innovation. The third issue »Politics of Big Data« edited by Mark Coté, Paolo Gerbaudo, and Jennifer Pybus, critically examines the political and economic dimensions of Big Data and thus details its contestation. The contributions focus on the materialities and processes which manifest Big Data and explore forms of value beyond the state and capital. These range from open data initiatives, social media metrics, machine learning algorithms, data visualisation to data dashboards, critical data analysis, and new modes of data action research and practice.
This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: • Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation • Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data • Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining • Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing • Covers latest datasets for natural language processing and information retrieval for social media like Twitter The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology.
The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth. Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.