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Author: Aaron K. Baughman
Publisher: Springer
ISBN: 3319149989
Category : Computers
Languages : en
Pages : 452
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Book Description
This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.
Author: Aaron K. Baughman
Publisher: Springer
ISBN: 3319149989
Category : Computers
Languages : en
Pages : 452
Get Book Here
Book Description
This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.
Author: Valery A. Petrushin
Publisher: Springer Science & Business Media
ISBN: 1846287995
Category : Computers
Languages : en
Pages : 540
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Book Description
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
ISBN: 1420042556
Category : Computers
Languages : en
Pages : 354
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Book Description
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: Petra Perner
Publisher: Springer
ISBN: 3540362827
Category : Computers
Languages : en
Pages : 137
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Book Description
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: Stefanos Vrochidis
Publisher: John Wiley & Sons
ISBN: 111937698X
Category : Technology & Engineering
Languages : en
Pages : 376
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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.
Author: Zhongfei Zhang
Publisher: CRC Press
ISBN: 1584889675
Category : Computers
Languages : en
Pages : 320
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Book Description
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: Chabane Djeraba
Publisher: Springer Science & Business Media
ISBN: 1461511410
Category : Computers
Languages : en
Pages : 242
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Book Description
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: Lin Lin
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
With the explosion in the complexity and amount of pervasive multimedia data, there are high demands of multimedia services and applications in various areas for people to easily access and distribute multimedia data. Facing with abundance multimedia resources but inefficient and rather old-fashioned keyword-based information retrieval approaches, a content-based multimedia information retrieval (CBMIR) system is required to (i) reduce the dimension space for storage saving and computation reduction; (ii) advance multimedia learning methods to accurately identify target semantics for bridging the semantics between low-level/mid-level features and high-level semantics; and (iii) effectively search media content for dynamical media delivery and enable the extensive applications to be media-type driven. This research mainly focuses on multimedia data mining and retrieval system for multimedia databases by addressing some main challenges, such as data imbalance, data quality, semantic gap, user subjectivity and searching issues. Therefore, a novel CBMIR system is proposed in this dissertation. The proposed system utilizes both association rule mining (ARM) technique and multiple correspondence analysis (MCA) technique by taking into account both pattern discovery and statistical analysis. First, media content is represented by the global and local low-level and mid-level features and stored in the multimedia database. Second, a data filtering component is proposed in the system to improve the data quality and reduce the data imbalance. To be specific, the proposed filtering step is able to vertically select features and horizontally prune instances in multimedia databases. Third, a new learning and classification method mining weighted association rules is proposed in the retrieval system. The MCA-based correlation is used to generate and select the weighted N-feature-value pair rules, where the N varies from one to many. Forth, a ranking method independent of classifiers is proposed in the system to sort the retrieved results and put the most interesting ones on the top of the browsing list. Finally, a user interface is implemented in CBMIR system that allows the user to choose his/her interested concept, searches media based on the target concept, ranks the retrieved segments using the proposed ranking algorithm, and then displays the top-ranked segments to the user. The system is experimented with various high-level semantics from TRECVID benchmark data sets. TRECVID sound and vision data is a large data set, includes various types of videos, and has very rich semantics. Overall, the proposed system achieves promising results in comparison with the other well-known methods. Moreover, experiments that compare each component with some other famous algorithms are conducted. The experimental results show that all proposed components improve the functionalities of the CBMIR system, and the proposed system reaches effectiveness, robustness and efficiency for a high-dimensional multimedia database.
Author: Wahiba Ben Abdessalem Karaa
Publisher: CRC Press
ISBN: 1315399725
Category : Computers
Languages : en
Pages : 260
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Book Description
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: Vibha Lakshmikantha
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659139116
Category :
Languages : en
Pages : 172
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Book Description
Database mining refers to extracting previously unrecognized information from data stored in conventional databases. Multimedia data mining deals with the extraction of implicit knowledge, multimedia data relationships, or other patterns not explicitly stored in multimedia databases. Three specific kinds of multimedia databases like image, video and remote sensed image are dealt with. A simple kind of multimedia database i.e., static image, where each mammogram is a set of four images is considered. Statistical analysis is performed on them to classify them as normal, benign and malign. Next a more complex database like video is considered, where it begins with a slow moving video clip and then move towards a faster moving video clip, in identifying and tracking objects. A specialized multimedia data is chosen, where an image obtained from a remote sensed satellite. The image is segmented into distinct regions like barren land, vegetative area, water bodies etc., and then we count the number of trees in the vegetative area. The analysis and Literature Survey are useful for students and research community, who are working on Data Mining, signal processing and Multimedia Mining.
