Supervised Descriptive Pattern Mining

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Supervised Descriptive Pattern Mining

Sebastián Ventura,José María Luna
Supervised Descriptive Pattern Mining Book PDF

Author : Sebastián Ventura,José María Luna
Publisher : Springer
Page : 185 pages
File Size : 54,6 Mb
Release : 2018-10-05
Category : Computers
ISBN : 9783319981406

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Supervised Descriptive Pattern Mining by Sebastián Ventura,José María Luna Pdf

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

R. Uday Kiran,Philippe Fournier-Viger,Jose M. Luna,Jerry Chun-Wei Lin,Anirban Mondal
Periodic Pattern Mining Book PDF

Author : R. Uday Kiran,Philippe Fournier-Viger,Jose M. Luna,Jerry Chun-Wei Lin,Anirban Mondal
Publisher : Springer Nature
Page : 263 pages
File Size : 42,5 Mb
Release : 2021-10-29
Category : Computers
ISBN : 9789811639647

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Periodic Pattern Mining by R. Uday Kiran,Philippe Fournier-Viger,Jose M. Luna,Jerry Chun-Wei Lin,Anirban Mondal Pdf

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.

Foundations of Rule Learning

Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač
Foundations of Rule Learning Book PDF

Author : Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač
Publisher : Springer Science & Business Media
Page : 345 pages
File Size : 47,9 Mb
Release : 2012-11-06
Category : Computers
ISBN : 9783540751977

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Foundations of Rule Learning by Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač Pdf

Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning. The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.

Advanced Data Mining and Applications

Jianxin Li,Sen Wang,Shaowen Qin,Xue Li,Shuliang Wang
Advanced Data Mining and Applications Book PDF

Author : Jianxin Li,Sen Wang,Shaowen Qin,Xue Li,Shuliang Wang
Publisher : Springer Nature
Page : 894 pages
File Size : 51,6 Mb
Release : 2019-11-16
Category : Computers
ISBN : 9783030352318

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Advanced Data Mining and Applications by Jianxin Li,Sen Wang,Shaowen Qin,Xue Li,Shuliang Wang Pdf

This book constitutes the proceedings of the 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, held in Dalian, China in November 2019. The 39 full papers presented together with 26 short papers and 2 demo papers were carefully reviewed and selected from 170 submissions. The papers were organized in topical sections named: Data Mining Foundations; Classification and Clustering Methods; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical and Healthcare Data/Decision Analytics; and Other Applications.

Computational Music Analysis

David Meredith
Computational Music Analysis Book PDF

Author : David Meredith
Publisher : Springer
Page : 480 pages
File Size : 51,7 Mb
Release : 2015-10-27
Category : Computers
ISBN : 9783319259314

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Computational Music Analysis by David Meredith Pdf

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

Mehmed Kantardzic
Data Mining Book PDF

Author : Mehmed Kantardzic
Publisher : John Wiley & Sons
Page : 656 pages
File Size : 42,7 Mb
Release : 2019-10-23
Category : Computers
ISBN : 9781119516071

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Data Mining by Mehmed Kantardzic Pdf

Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.

Machine Learning and Data Mining for Sports Analytics

Ulf Brefeld,Jesse Davis,Jan Van Haaren,Albrecht Zimmermann
Machine Learning and Data Mining for Sports Analytics Book PDF

Author : Ulf Brefeld,Jesse Davis,Jan Van Haaren,Albrecht Zimmermann
Publisher : Springer Nature
Page : 211 pages
File Size : 40,7 Mb
Release : 2022-05-03
Category : Computers
ISBN : 9783031020445

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Machine Learning and Data Mining for Sports Analytics by Ulf Brefeld,Jesse Davis,Jan Van Haaren,Albrecht Zimmermann Pdf

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

Magy Seif El-Nasr,Anders Drachen,Alessandro Canossa
Game Analytics Book PDF

Author : Magy Seif El-Nasr,Anders Drachen,Alessandro Canossa
Publisher : Springer Science & Business Media
Page : 792 pages
File Size : 42,8 Mb
Release : 2013-03-30
Category : Computers
ISBN : 9781447147695

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Game Analytics by Magy Seif El-Nasr,Anders Drachen,Alessandro Canossa Pdf

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

Manuel Graña,José Manuel López-Guede,Oier Etxaniz,Álvaro Herrero,Héctor Quintián,Emilio Corchado
International Joint Conference SOCO 16 CISIS 16 ICEUTE 16 Book PDF

Author : Manuel Graña,José Manuel López-Guede,Oier Etxaniz,Álvaro Herrero,Héctor Quintián,Emilio Corchado
Publisher : Springer
Page : 813 pages
File Size : 50,9 Mb
Release : 2016-10-10
Category : Technology & Engineering
ISBN : 9783319473642

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International Joint Conference SOCO’16-CISIS’16-ICEUTE’16 by Manuel Graña,José Manuel López-Guede,Oier Etxaniz,Álvaro Herrero,Héctor Quintián,Emilio Corchado Pdf

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

Christos Dimitrakakis,Aris Gkoulalas-Divanis,Aikaterini Mitrokotsa,Vassilios S. Verykios,Yücel Saygin
Privacy and Security Issues in Data Mining and Machine Learning Book PDF

Author : Christos Dimitrakakis,Aris Gkoulalas-Divanis,Aikaterini Mitrokotsa,Vassilios S. Verykios,Yücel Saygin
Publisher : Springer Science & Business Media
Page : 148 pages
File Size : 42,7 Mb
Release : 2011-03-17
Category : Business & Economics
ISBN : 9783642198953

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Privacy and Security Issues in Data Mining and Machine Learning by Christos Dimitrakakis,Aris Gkoulalas-Divanis,Aikaterini Mitrokotsa,Vassilios S. Verykios,Yücel Saygin Pdf

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.

Pattern Mining with Evolutionary Algorithms

Sebastián Ventura,José María Luna
Pattern Mining with Evolutionary Algorithms Book PDF

Author : Sebastián Ventura,José María Luna
Publisher : Springer
Page : 190 pages
File Size : 48,9 Mb
Release : 2016-06-13
Category : Computers
ISBN : 9783319338583

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Pattern Mining with Evolutionary Algorithms by Sebastián Ventura,José María Luna Pdf

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

Claude Sammut,Geoffrey I. Webb
Encyclopedia of Machine Learning Book PDF

Author : Claude Sammut,Geoffrey I. Webb
Publisher : Springer Science & Business Media
Page : 1061 pages
File Size : 45,9 Mb
Release : 2011-03-28
Category : Computers
ISBN : 9780387307688

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Encyclopedia of Machine Learning by Claude Sammut,Geoffrey I. Webb Pdf

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

Ricardo Cerri,Ronaldo C. Prati
Intelligent Systems Book PDF

Author : Ricardo Cerri,Ronaldo C. Prati
Publisher : Springer Nature
Page : 682 pages
File Size : 43,5 Mb
Release : 2020-10-15
Category : Computers
ISBN : 9783030613808

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Intelligent Systems by Ricardo Cerri,Ronaldo C. Prati Pdf

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

Charu C. Aggarwal,Jiawei Han
Frequent Pattern Mining Book PDF

Author : Charu C. Aggarwal,Jiawei Han
Publisher : Springer
Page : 480 pages
File Size : 45,8 Mb
Release : 2014-08-29
Category : Computers
ISBN : 9783319078212

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Frequent Pattern Mining by Charu C. Aggarwal,Jiawei Han Pdf

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

Sašo Džeroski,Panče Panov,Dragi Kocev,Ljupčo Todorovski
Discovery Science Book PDF

Author : Sašo Džeroski,Panče Panov,Dragi Kocev,Ljupčo Todorovski
Publisher : Springer
Page : 383 pages
File Size : 50,9 Mb
Release : 2014-09-27
Category : Computers
ISBN : 9783319118123

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Discovery Science by Sašo Džeroski,Panče Panov,Dragi Kocev,Ljupčo Todorovski Pdf

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.