Multimedia Data Mining And Analytics
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Multimedia Data Mining And Analytics
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Author : Aaron K. Baughman
language : en
Publisher: Springer
Release Date : 2015-03-31
Multimedia Data Mining And Analytics written by Aaron K. Baughman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-31 with Computers categories.
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.
Multimedia Data Mining And Analytics
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Author : Aaron K. Baughman
language : en
Publisher:
Release Date : 2015
Multimedia Data Mining And Analytics written by Aaron K. Baughman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Data mining categories.
This authoritative text/reference 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. Presenting a detailed exploration into the progression of the field, the book 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. Topics and features: · Contains contributions from an international selection of pre-eminent authorities in the field · Reviews how disruptive 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 multimedia 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 The illuminating viewpoints presented in this comprehensive volume will be of great interest to researchers and graduate students involved in machine learning and pattern recognition, as well as to professional multimedia analysts and software developers.
Big Data Analytics For Large Scale Multimedia Search
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Author : Stefanos Vrochidis
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-18
Big Data Analytics For Large Scale Multimedia Search written by Stefanos Vrochidis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-18 with Technology & Engineering categories.
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 Data Mining And Knowledge Discovery
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Author : Valery A. Petrushin
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-20
Multimedia Data Mining And Knowledge Discovery written by Valery A. Petrushin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-20 with Computers categories.
This tightly-edited collection of papers from leading researchers worldwide provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research. Consisting of an introductory section and four topical parts, the book 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. Written with graduates in mind, this much needed comprehensive reflection of the current state of multimedia data mining and knowledge discovery will also be a valuable resource for researchers in the field. This book provides an overview of the current state of the art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research. Topics and Features: - Features a comprehensive introduction to multimedia data mining and its relevance today; - presents a global perspective of the field and its various components; - provides broad, yet thorough and detailed coverage of the subject; - numerous chapters reference websites with supplementary materials and demonstrations; - explores multimedia data exploration, multimedia data modeling and evaluation, and visualization; - offers an entire part devoted to applications and case studies. Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.
Data Mining On Multimedia Data
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2003-07-01
Data Mining On Multimedia Data written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-01 with Computers categories.
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.
Multimedia Data Mining
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Author : Zhongfei Zhang
language : en
Publisher: CRC Press
Release Date : 2008-12-02
Multimedia Data Mining written by Zhongfei Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-02 with Computers categories.
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
Data Mining
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Author : Sushmita Mitra
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-07
Data Mining written by Sushmita Mitra and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-07 with Computers categories.
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
Multimedia Mining
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Author : Chabane Djeraba
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Multimedia Mining written by Chabane Djeraba and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
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.
Multimedia Data Mining And Retrieval For Multimedia Databases Using Associations And Correlations
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Author : Lin Lin
language : en
Publisher:
Release Date : 2010
Multimedia Data Mining And Retrieval For Multimedia Databases Using Associations And Correlations written by Lin Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
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.
Multimedia Information Extraction
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Author : Mark T. Maybury
language : en
Publisher: John Wiley & Sons
Release Date : 2012-07-11
Multimedia Information Extraction written by Mark T. Maybury and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-11 with Computers categories.
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.