Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4) human-computer affective multimedia interaction. Its 15 chapters cover key topics such as content creation, annotation and modeling for the semantic web, multimedia content understanding, and efficiency and scalability. Fostering a deeper understanding of a popular area of research, the text: Describes state-of-the-art schemes and applications Supplies authoritative guidance on research and deployment issues Presents novel methods and applications in an informative and reproducible way Contains numerous examples, illustrations, and tables summarizing results from quantitative studies Considers ongoing trends and designates future challenges and research perspectives Includes bibliographic links for further exploration Uses both SI and US units Ideal for engineers and scientists specializing in the design of multimedia systems, software applications, and image/video analysis and processing technologies, Semantic Multimedia Analysis and Processing aids researchers, practitioners, and developers in finding innovative solutions to existing problems, opening up new avenues of research in uncharted waters.

This book constitutes the refereed proceedings of the Second International Conference on Semantics and Digital Media Technologies, SAMT 2007, held in Genoa, Italy, in December 2007. The conference brings together forums, projects, institutions and individuals investigating the integration of knowledge, semantics and low-level multimedia processing, including new emerging media and application areas. The papers are organized in topical sections.

As technology becomes increasingly intelligent, various factors within the field of data science are seeing significant transformation. Process analysis is one area that is undergoing substantial development due to the implementation of semantic reasoning and web technologies. The congruence of these two systems has created various applications and developments in data processing and analysis across several professional fields. Applications and Developments in Semantic Process Mining is an essential reference source that discusses the improvement of process mining algorithms through the implementation of semantic modeling and representation. Featuring research on topics such as domain ontologies, fuzzy modeling, and information extraction, the book takes into account the different stages of process mining and its application in real time and then expounds the classical process mining techniques to semantical preparation of the extracted models for further analysis and querying at a more abstract level. The book provides a wide-ranging idea of the application and development of semantic process mining that is expected to be beneficial and used by professionals, software and data engineers, software developers, IT experts, business owners and entrepreneurs, and process analysts.

WearepleasedtowelcomeyoutotheproceedingsoftheThirdInternationalC- ference onSemantic andDigital Media Technologiesheld inKoblenz,Germany. The SAMT agenda brings together researchers at extreme ends of the - mantic multimedia spectrum. At one end, the Semantic Web and its supporting technologies are becoming established in both the open data environment and within specialist domains, such as corporate intranet search, e-Science (parti- larly life sciences), and cultural heritage. To facilitate the world-wide sharing of media, W3C is developing standard ways of denoting fragments of audio/visual content and of specifying and associating semantics with these. At the other end of the spectrum, media analysis tools continue to grow in sophistication, identifying features that can then be associated with explicit semantics, be they expressed formally or informally, using proprietary formats or open standards. Recent progress at these two fronts of the SAMT spectrum means that research spanningthesemanticgapisnowofvitalimportancetofeedtherealapplications that are emerging. This conference also represents a step towards bridging the gap between the research cultures and their respective approaches at both ends of the spectrum. The papers selected show that SAMT is able to attract researchers from media analysis, who see the bene?ts that more explicit semantics can provide, as well as researchers from knowledge engineering who realize that, while a picture can be expressed as a thousand concepts, a million morearewaiting to be extracted.

This book constitutes the refereed proceedings of the First International Conference on Semantics and Digital Media Technologies, SAMT 2006, held in Athens, Greece in December 2006. The 17 revised full papers address a wide area of integrative research on new knowledge-based forms of digital media systems, semantics, and low-level multimedia processing.

In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.

The Encyclopedia of Image Processing presents a vast collection of well-written articles covering image processing fundamentals (e.g. color theory, fuzzy sets, cryptography) and applications (e.g. geographic information systems, traffic analysis, forgery detection). Image processing advances have enabled many applications in healthcare, avionics, robotics, natural resource discovery, and defense, which makes this text a key asset for both academic and industrial libraries and applied scientists and engineers working in any field that utilizes image processing. Written by experts from both academia and industry, it is structured using the ACM Computing Classification System (CCS) first published in 1988, but most recently updated in 2012.