Supervised Descriptive Pattern Mining

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Supervised Descriptive Pattern Mining

Author : Sebastián Ventura
Publisher : Springer
ISBN 13 : 3319981404
Total Pages : 185 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Supervised Descriptive Pattern Mining by : Sebastián Ventura

Download or read book Supervised Descriptive Pattern Mining written by Sebastián Ventura and published by Springer. This book was released on 2018-10-05 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a general and comprehensible overview of supervised descriptive pattern mining, considering classic algorithms and those based on heuristics. It provides some formal definitions and a general idea about patterns, pattern mining, the usefulness of patterns in the knowledge discovery process, as well as a brief summary on the tasks related to supervised descriptive pattern mining. It also includes a detailed description on the tasks usually grouped under the term supervised descriptive pattern mining: subgroups discovery, contrast sets and emerging patterns. Additionally, this book includes two tasks, class association rules and exceptional models, that are also considered within this field. A major feature of this book is that it provides a general overview (formal definitions and algorithms) of all the tasks included under the term supervised descriptive pattern mining. It considers the analysis of different algorithms either based on heuristics or based on exhaustive search methodologies for any of these tasks. This book also illustrates how important these techniques are in different fields, a set of real-world applications are described. Last but not least, some related tasks are also considered and analyzed. The final aim of this book is to provide a general review of the supervised descriptive pattern mining field, describing its tasks, its algorithms, its applications, and related tasks (those that share some common features). This book targets developers, engineers and computer scientists aiming to apply classic and heuristic-based algorithms to solve different kinds of pattern mining problems and apply them to real issues. Students and researchers working in this field, can use this comprehensive book (which includes its methods and tools) as a secondary textbook.

Periodic Pattern Mining

Author : R. Uday Kiran
Publisher : Springer Nature
ISBN 13 : 9811639647
Total Pages : 263 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Periodic Pattern Mining by : R. Uday Kiran

Download or read book Periodic Pattern Mining written by R. Uday Kiran and published by Springer Nature. This book was released on 2021-10-29 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications. The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed. The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques. The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.

Associative Pattern Mining for Supervised Learning

Author : Singh Harpreet
Publisher :
ISBN 13 :
Total Pages : 252 pages
Book Rating : 4.:/5 (926 download)

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Book Synopsis Associative Pattern Mining for Supervised Learning by : Singh Harpreet

Download or read book Associative Pattern Mining for Supervised Learning written by Singh Harpreet and published by . This book was released on 2010 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Music Analysis

Author : David Meredith
Publisher : Springer
ISBN 13 : 3319259318
Total Pages : 483 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Computational Music Analysis by : David Meredith

Download or read book Computational Music Analysis written by David Meredith and published by Springer. This book was released on 2015-10-27 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.

Data Mining

Author : Mehmed Kantardzic
Publisher : John Wiley & Sons
ISBN 13 : 0470890452
Total Pages : 554 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Data Mining by : Mehmed Kantardzic

Download or read book Data Mining written by Mehmed Kantardzic and published by John Wiley & Sons. This book was released on 2011-08-16 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades. If you are an instructor or professor and would like to obtain instructor’s materials, please visit http://booksupport.wiley.com If you are an instructor or professor and would like to obtain a solutions manual, please send an email to: [email protected]

Machine Learning and Data Mining for Sports Analytics

Author : Ulf Brefeld
Publisher : Springer Nature
ISBN 13 : 3031020448
Total Pages : 211 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Machine Learning and Data Mining for Sports Analytics by : Ulf Brefeld

Download or read book Machine Learning and Data Mining for Sports Analytics written by Ulf Brefeld and published by Springer Nature. This book was released on 2022-05-03 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 8th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2021, held as virtual event in September 2021. The 12 full papers and 4 short papers presented were carefully reviewed and selected from 29 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.

Game Analytics

Author : Magy Seif El-Nasr
Publisher : Springer Science & Business Media
ISBN 13 : 1447147693
Total Pages : 792 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Game Analytics by : Magy Seif El-Nasr

Download or read book Game Analytics written by Magy Seif El-Nasr and published by Springer Science & Business Media. This book was released on 2013-03-30 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

International Joint Conference SOCO’16-CISIS’16-ICEUTE’16

Author : Manuel Graña
Publisher : Springer
ISBN 13 : 3319473646
Total Pages : 813 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis International Joint Conference SOCO’16-CISIS’16-ICEUTE’16 by : Manuel Graña

Download or read book International Joint Conference SOCO’16-CISIS’16-ICEUTE’16 written by Manuel Graña and published by Springer. This book was released on 2016-10-10 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2016, CISIS 2016 and ICEUTE 2016, all conferences held in the beautiful and historic city of San Sebastián (Spain), in October 2016. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 11th SOCO 2016 International Program Committee selected 45 papers. In this relevant edition a special emphasis was put on the organization of special sessions. Two special session was organized related to relevant topics as: Optimization, Modeling and Control Systems by Soft Computing and Soft Computing Methods in Manufacturing and Management Systems. The aim of the 9th CISIS 2016 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and Data Mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2016 International Program Committee selected 20 papers. In the case of 7th ICEUTE 2016, the International Program Committee selected 14 papers.

Privacy and Security Issues in Data Mining and Machine Learning

Author : Christos Dimitrakakis
Publisher : Springer Science & Business Media
ISBN 13 : 3642198953
Total Pages : 148 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Privacy and Security Issues in Data Mining and Machine Learning by : Christos Dimitrakakis

Download or read book Privacy and Security Issues in Data Mining and Machine Learning written by Christos Dimitrakakis and published by Springer Science & Business Media. This book was released on 2011-03-17 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International ECML/PKDD Workshop on Privacy and Security Issues in Data Mining and Machine Learning, PSDML 2010, held in Barcelona, Spain, in September 2010. The 11 revised full papers presented were carefully reviewed and selected from 21 submissions. The papers range from data privacy to security applications, focusing on detecting malicious behavior in computer systems.

Mathematics and Computation in Music

Author : Thomas Noll
Publisher : Springer Nature
ISBN 13 : 3031606388
Total Pages : 474 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Mathematics and Computation in Music by : Thomas Noll

Download or read book Mathematics and Computation in Music written by Thomas Noll and published by Springer Nature. This book was released on with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Pattern Mining with Evolutionary Algorithms

Author : Sebastián Ventura
Publisher : Springer
ISBN 13 : 3319338587
Total Pages : 199 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Pattern Mining with Evolutionary Algorithms by : Sebastián Ventura

Download or read book Pattern Mining with Evolutionary Algorithms written by Sebastián Ventura and published by Springer. This book was released on 2016-06-13 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.

Encyclopedia of Machine Learning

Author : Claude Sammut
Publisher : Springer Science & Business Media
ISBN 13 : 0387307680
Total Pages : 1061 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Encyclopedia of Machine Learning by : Claude Sammut

Download or read book Encyclopedia of Machine Learning written by Claude Sammut and published by Springer Science & Business Media. This book was released on 2011-03-28 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Intelligent Systems

Author : Ricardo Cerri
Publisher : Springer Nature
ISBN 13 : 3030613801
Total Pages : 682 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Intelligent Systems by : Ricardo Cerri

Download or read book Intelligent Systems written by Ricardo Cerri and published by Springer Nature. This book was released on 2020-10-15 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 12319 and 12320 constitutes the proceedings of the 9th Brazilian Conference on Intelligent Systems, BRACIS 2020, held in Rio Grande, Brazil, in October 2020. The total of 90 papers presented in these two volumes was carefully reviewed and selected from 228 submissions. The contributions are organized in the following topical section: Part I: Evolutionary computation, metaheuristics, constrains and search, combinatorial and numerical optimization; neural networks, deep learning and computer vision; and text mining and natural language processing. Part II: Agent and multi-agent systems, planning and reinforcement learning; knowledge representation, logic and fuzzy systems; machine learning and data mining; and multidisciplinary artificial and computational intelligence and applications. Due to the Corona pandemic BRACIS 2020 was held as a virtual event.

Frequent Pattern Mining

Author : Charu C. Aggarwal
Publisher : Springer
ISBN 13 : 3319078216
Total Pages : 480 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Frequent Pattern Mining by : Charu C. Aggarwal

Download or read book Frequent Pattern Mining written by Charu C. Aggarwal and published by Springer. This book was released on 2014-08-29 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

Discovery Science

Author : Sašo Džeroski
Publisher : Springer
ISBN 13 : 3319118129
Total Pages : 383 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Discovery Science by : Sašo Džeroski

Download or read book Discovery Science written by Sašo Džeroski and published by Springer. This book was released on 2014-09-27 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2014, held in Bled, Slovenia, in October 2014. The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The papers cover topics such as: computational scientific discovery; data mining and knowledge discovery; machine learning and statistical methods; computational creativity; mining scientific data; data and knowledge visualization; knowledge discovery from scientific literature; mining text, unstructured and multimedia data; mining structured and relational data; mining temporal and spatial data; mining data streams; network analysis; discovery informatics; discovery and experimental workflows; knowledge capture and scientific ontologies; data and knowledge integration; logic and philosophy of scientific discovery; and applications of computational methods in various scientific domains.

Exploiting the Power of Group Differences

Author : Guozhu Dong
Publisher : Springer Nature
ISBN 13 : 303101913X
Total Pages : 135 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Exploiting the Power of Group Differences by : Guozhu Dong

Download or read book Exploiting the Power of Group Differences written by Guozhu Dong and published by Springer Nature. This book was released on 2022-05-31 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents pattern-based problem-solving methods for a variety of machine learning and data analysis problems. The methods are all based on techniques that exploit the power of group differences. They make use of group differences represented using emerging patterns (aka contrast patterns), which are patterns that match significantly different numbers of instances in different data groups. A large number of applications outside of the computing discipline are also included. Emerging patterns (EPs) are useful in many ways. EPs can be used as features, as simple classifiers, as subpopulation signatures/characterizations, and as triggering conditions for alerts. EPs can be used in gene ranking for complex diseases since they capture multi-factor interactions. The length of EPs can be used to detect anomalies, outliers, and novelties. Emerging/contrast pattern based methods for clustering analysis and outlier detection do not need distance metrics, avoiding pitfalls of the latter in exploratory analysis of high dimensional data. EP-based classifiers can achieve good accuracy even when the training datasets are tiny, making them useful for exploratory compound selection in drug design. EPs can serve as opportunities in opportunity-focused boosting and are useful for constructing powerful conditional ensembles. EP-based methods often produce interpretable models and results. In general, EPs are useful for classification, clustering, outlier detection, gene ranking for complex diseases, prediction model analysis and improvement, and so on. EPs are useful for many tasks because they represent group differences, which have extraordinary power. Moreover, EPs represent multi-factor interactions, whose effective handling is of vital importance and is a major challenge in many disciplines. Based on the results presented in this book, one can clearly say that patterns are useful, especially when they are linked to issues of interest. We believe that many effective ways to exploit group differences' power still remain to be discovered. Hopefully this book will inspire readers to discover such new ways, besides showing them existing ways, to solve various challenging problems.

Java Data Mining: Strategy, Standard, and Practice

Author : Mark F. Hornick
Publisher : Elsevier
ISBN 13 : 0080495915
Total Pages : 545 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Java Data Mining: Strategy, Standard, and Practice by : Mark F. Hornick

Download or read book Java Data Mining: Strategy, Standard, and Practice written by Mark F. Hornick and published by Elsevier. This book was released on 2010-07-26 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard. Data mining introduction - an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems JDM essentials - concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects JDM in practice - the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API Free, downloadable KJDM source code referenced in the book available here