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Book Multimedia Data Mining and Knowledge Discovery

Download or read book Multimedia Data Mining and Knowledge Discovery written by Valery A. Petrushin and published by Springer Science & Business Media. This book was released on 2007-10-20 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Multimedia Data Mining

Download or read book Multimedia Data Mining written by Zhongfei Zhang and published by CRC Press. This book was released on 2008-12-02 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Data Mining on Multimedia Data

Download or read book Data Mining on Multimedia Data written by Petra Perner and published by Springer. This book was released on 2003-07-01 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Multimedia Mining

    Book Details:
  • Author : Chabane Djeraba
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 1461511410
  • Pages : 242 pages

Download or read book Multimedia Mining written by Chabane Djeraba and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Data Mining

    Book Details:
  • Author : Sushmita Mitra
  • Publisher : John Wiley & Sons
  • Release : 2005-01-21
  • ISBN : 0471474886
  • Pages : 423 pages

Download or read book Data Mining written by Sushmita Mitra and published by John Wiley & Sons. This book was released on 2005-01-21 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Mining Multimedia and Complex Data

Download or read book Mining Multimedia and Complex Data written by Osmar R. Zaiane and published by Springer Science & Business Media. This book was released on 2003-10-13 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of thoroughly refereed revised papers selected from two international workshops on mining complex data: Multimedia Data Mining, MDM/KDD at KDD 2002 and Knowledge Discovery from Multimedia and Complex Data, KDMCD at PAKDD 2002. The 17 revised full papers presented together with a detailed introduction give a coherent survey of the state of the art in the area. Among the topics addressed are mining spatial multimedia data, mining audio data and multimedia support, mining image and video data, frameworks for multimedia mining, multimedia for information retrieval, and applications of multimedia mining.

Book Mining Multimedia Documents

Download or read book Mining Multimedia Documents written by Wahiba Ben Abdessalem Karaa and published by CRC Press. This book was released on 2017-04-21 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Data Mining and Knowledge Discovery Technologies

Download or read book Data Mining and Knowledge Discovery Technologies written by Taniar, David and published by IGI Global. This book was released on 2008-01-31 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: As information technology continues to advance in massive increments, the bank of information available from personal, financial, and business electronic transactions and all other electronic documentation and data storage is growing at an exponential rate. With this wealth of information comes the opportunity and necessity to utilize this information to maintain competitive advantage and process information effectively in real-world situations. Data Mining and Knowledge Discovery Technologies presents researchers and practitioners in fields such as knowledge management, information science, Web engineering, and medical informatics, with comprehensive, innovative research on data mining methods, structures, tools, and methods, the knowledge discovery process, and data marts, among many other cutting-edge topics.

Book Managing and Mining Multimedia Databases

Download or read book Managing and Mining Multimedia Databases written by Bhavani Thuraisingham and published by CRC Press. This book was released on 2001-06-28 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Advances in Knowledge Discovery and Data Mining

Download or read book Advances in Knowledge Discovery and Data Mining written by Jian Pei and published by Springer. This book was released on 2013-04-06 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 7818 + LNAI 7819 constitutes the refereed proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013, held in Gold Coast, Australia, in April 2013. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 363 submissions. They cover the general fields of data mining and KDD extensively, including pattern mining, classification, graph mining, applications, machine learning, feature selection and dimensionality reduction, multiple information sources mining, social networks, clustering, text mining, text classification, imbalanced data, privacy-preserving data mining, recommendation, multimedia data mining, stream data mining, data preprocessing and representation.

Book Advances in Knowledge Discovery and Data Mining

Download or read book Advances in Knowledge Discovery and Data Mining written by Joshua Zhexue Huang and published by Springer. This book was released on 2011-05-27 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.

Book Advanced Methods for Knowledge Discovery from Complex Data

Download or read book Advanced Methods for Knowledge Discovery from Complex Data written by Ujjwal Maulik and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.

Book Data Mining and Knowledge Discovery Handbook

Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2010-09-10 with total page 1269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Book Innovations in Big Data Mining and Embedded Knowledge

Download or read book Innovations in Big Data Mining and Embedded Knowledge written by Anna Esposito and published by Springer. This book was released on 2019-07-03 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies

Book Data Mining  Concepts and Techniques

Download or read book Data Mining Concepts and Techniques written by Jiawei Han and published by Elsevier. This book was released on 2011-06-09 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Book Data Mining for Multimedia Databases

    Book Details:
  • Author : Vibha Lakshmikantha
  • Publisher : LAP Lambert Academic Publishing
  • Release : 2012-07
  • ISBN : 9783659139116
  • Pages : 172 pages

Download or read book Data Mining for Multimedia Databases written by Vibha Lakshmikantha and published by LAP Lambert Academic Publishing. This book was released on 2012-07 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.