Advanced Data Mining Techniques For Compound Objects
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Advanced Data Mining Techniques
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Author : David L. Olson
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-01
Advanced Data Mining Techniques written by David L. Olson 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 2008-01-01 with Business & Economics categories.
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.
Advanced Methods For Knowledge Discovery From Complex Data
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Author : Ujjwal Maulik
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-06
Advanced Methods For Knowledge Discovery From Complex Data written by Ujjwal Maulik 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 2006-05-06 with Computers categories.
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.
Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence
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Author : Trivedi, Shrawan Kumar
language : en
Publisher: IGI Global
Release Date : 2017-02-14
Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence written by Trivedi, Shrawan Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-14 with Computers categories.
The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.
Game Analytics
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Author : Magy Seif El-Nasr
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-30
Game Analytics written by Magy Seif El-Nasr 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 2013-03-30 with Computers categories.
Developing a successful game in today’s market is a challenging endeavor. Thousands of titles are published yearly, all competing for players’ time and attention. Game analytics has emerged in the past few years as one of the main resources for ensuring game quality, maximizing success, understanding player behavior and enhancing the quality of the player experience. It has led to a paradigm shift in the development and design strategies of digital games, bringing data-driven intelligence practices into the fray for informing decision making at operational, tactical and strategic levels. Game Analytics - Maximizing the Value of Player Data is the first book on the topic of game analytics; the process of discovering and communicating patterns in data towards evaluating and driving action, improving performance and solving problems in game development and game research. Written by over 50 international experts from industry and research, it covers a comprehensive range of topics across more than 30 chapters, providing an in-depth discussion of game analytics and its practical applications. Topics covered include monetization strategies, design of telemetry systems, analytics for iterative production, game data mining and big data in game development, spatial analytics, visualization and reporting of analysis, player behavior analysis, quantitative user testing and game user research. This state-of-the-art volume is an essential source of reference for game developers and researchers. Key takeaways include: Thorough introduction to game analytics; covering analytics applied to data on players, processes and performance throughout the game lifecycle. In-depth coverage and advice on setting up analytics systems and developing good practices for integrating analytics in game-development and -management. Contributions by leading researchers and experienced professionals from the industry, including Ubisoft, Sony, EA, Bioware, Square Enix, THQ, Volition, and PlayableGames. Interviews with experienced industry professionals on how they use analytics to create hit games.
Advanced Data Mining Techniques
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Author : Dr.P.Alagesh Kannan
language : en
Publisher: SK Research Group of Companies
Release Date : 2023-08-07
Advanced Data Mining Techniques written by Dr.P.Alagesh Kannan and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-07 with Computers categories.
Dr.P.Alagesh Kannan, Assistant Professor, Department of Computer Science, Madurai Kamaraj University College, Madurai,Tamil Nadu, India. Dr.J.Saravanesh, Assistant Professor, Department of Computer Science, Madurai Kamaraj University College, Madurai,Tamil Nadu, India.
Advanced Data Mining Technologies In Bioinformatics
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Author : Hui-Huang Hsu
language : en
Publisher: IGI Global
Release Date : 2006-01-01
Advanced Data Mining Technologies In Bioinformatics written by Hui-Huang Hsu and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Computers categories.
"This book covers research topics of data mining on bioinformatics presenting the basics and problems of bioinformatics and applications of data mining technologies pertaining to the field"--Provided by publisher.
Advanced Data Mining And Applications
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Author : Xue Li
language : en
Publisher: Springer
Release Date : 2006-07-27
Advanced Data Mining And Applications written by Xue Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-27 with Computers categories.
Here are the proceedings of the 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China, August 2006. The book presents 41 revised full papers and 74 revised short papers together with 4 invited papers. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, and more.
Graph Data Mining
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Author : Qi Xuan
language : en
Publisher: Springer Nature
Release Date : 2021-07-15
Graph Data Mining written by Qi Xuan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-15 with Computers categories.
Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks. Graph data mining is used to discover useful information and knowledge from graph data. The complications of nodes, links and the semi-structure form present challenges in terms of the computation tasks, e.g., node classification, link prediction, and graph classification. In this context, various advanced techniques, including graph embedding and graph neural networks, have recently been proposed to improve the performance of graph data mining. This book provides a state-of-the-art review of graph data mining methods. It addresses a current hot topic – the security of graph data mining – and proposes a series of detection methods to identify adversarial samples in graph data. In addition, it introduces readers to graph augmentation and subgraph networks to further enhance the models, i.e., improve their accuracy and robustness. Lastly, the book describes the applications of these advanced techniques in various scenarios, such as traffic networks, social and technical networks, and blockchains.
Scientific Data Mining
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Author : Chandrika Kamath
language : en
Publisher: SIAM
Release Date : 2009-01-01
Scientific Data Mining written by Chandrika Kamath and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with Mathematics categories.
Chandrika Kamath describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains. Starting with a survey of analysis problems in different applications, it identifies the common themes across these domains.
New Frontiers In Mining Complex Patterns
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Author : Michelangelo Ceci
language : en
Publisher: Springer
Release Date : 2016-05-17
New Frontiers In Mining Complex Patterns written by Michelangelo Ceci and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-17 with Computers categories.
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2015, held in conjunction with ECML-PKDD 2015 in Porto, Portugal, in September 2015. The 15 revised full papers presented together with one invited talk were carefully reviewed and selected from 19 submissions. They illustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: data stream mining, classification, mining complex data, and sequences.