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| Author | : Zhongfei Zhang |
| Publisher | : CRC Press |
| Total Pages | : 320 |
| Release | : 2008-12-02 |
| Genre | : Computers |
| ISBN | : 1584889675 |
Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines multimedia data mining, its theory, and its applications. Two of the most active researchers in multimedia data mining explore how this young area has rapidly developed in recent years.The book first discusses the theore
| Author | : Valery A. Petrushin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 540 |
| Release | : 2007-10-20 |
| Genre | : Computers |
| ISBN | : 1846287995 |
This volume provides an overview of multimedia data mining and knowledge discovery and discusses the variety of hot topics in multimedia data mining research. It describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field.
| Author | : Bhavani Thuraisingham |
| Publisher | : CRC Press |
| Total Pages | : 354 |
| Release | : 2001-06-28 |
| Genre | : Computers |
| ISBN | : 1420042556 |
There is now so much data on the Web that managing it with conventional tools is becoming almost impossible. To manage this data, provide interoperability and warehousing between multiple data sources and systems, and extract information from the databases and warehouses, various tools are being developed. In fact, developments in multimedia databa
| Author | : Sushmita Mitra |
| Publisher | : John Wiley & Sons |
| Total Pages | : 423 |
| Release | : 2005-01-21 |
| Genre | : Computers |
| ISBN | : 0471474886 |
First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining
| Author | : Chabane Djeraba |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 258 |
| Release | : 2002-11-30 |
| Genre | : Computers |
| ISBN | : 9781402072475 |
Multimedia Mining: A Highway to Intelligent Multimedia Documents brings together experts in digital media content analysis, state-of-art data mining and knowledge discovery in multimedia database systems, knowledge engineers and domain experts from diverse applied disciplines. Multimedia documents are ubiquitous and often required, if not essential, in many applications today. This phenomenon has made multimedia documents widespread and extremely large. There are tools for managing and searching within these collections, but the need for tools to extract hidden useful knowledge embedded within multimedia objects is becoming pressing and central for many decision-making applications. The tools needed today are tools for discovering relationships between objects or segments within multimedia document components, such as classifying images based on their content, extracting patterns in sound, categorizing speech and music, and recognizing and tracking objects in video streams.
| Author | : Petra Perner |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 137 |
| Release | : 2002-12-13 |
| Genre | : Computers |
| ISBN | : 3540003177 |
Despite being a young field of research and development, data mining has proved to be a successful approach to extracting knowledge from huge collections of structured digital data collection as usually stored in databases. Whereas data mining was done in early days primarily on numerical data, nowadays multimedia and Internet applications drive the need to develop data mining methods and techniques that can work on all kinds of data such as documents, images, and signals. This book introduces the basic concepts of mining multimedia data and demonstrates how to apply these methods in various application fields. It is written for students, ambitioned professionals from industry and medicine, and for scientists who want to contribute R&D work to the field or apply this new technology.
| Author | : Wahiba Ben Abdessalem Karaa |
| Publisher | : CRC Press |
| Total Pages | : 243 |
| Release | : 2017-04-21 |
| Genre | : Technology & Engineering |
| ISBN | : 1315399733 |
The information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them. Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.
| Author | : Stefanos Vrochidis |
| Publisher | : John Wiley & Sons |
| Total Pages | : 372 |
| Release | : 2019-05-28 |
| Genre | : Technology & Engineering |
| ISBN | : 1119376971 |
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.
| Author | : Mark T. Maybury |
| Publisher | : John Wiley & Sons |
| Total Pages | : 436 |
| Release | : 2012-07-11 |
| Genre | : Computers |
| ISBN | : 111821952X |
The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance. While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and video, these advances have been explored in largely independent research communities who have addressed extracting information from single media (e.g., text, imagery, audio). And yet users need to search for concepts across individual media, author multimedia artifacts, and perform multimedia analysis in many domains. This collection is intended to serve several purposes, including reporting the current state of the art, stimulating novel research, and encouraging cross-fertilization of distinct research disciplines. The collection and integration of a common base of intellectual material will provide an invaluable service from which to teach a future generation of cross disciplinary media scientists and engineers.
| Author | : Charu C. Aggarwal |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 527 |
| Release | : 2012-02-03 |
| Genre | : Computers |
| ISBN | : 1461432235 |
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
