Download or read book Complex Pattern Mining written by Annalisa Appice and published by Springer Nature. This book was released on 2020-01-14 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the challenges facing current research in knowledge discovery and data mining posed by the huge volumes of complex data now gathered in various real-world applications (e.g., business process monitoring, cybersecurity, medicine, language processing, and remote sensing). The book consists of 14 chapters covering the latest research by the authors and the research centers they represent. It illustrates techniques and algorithms that have recently been developed to preserve the richness of the data and allow us to efficiently and effectively identify the complex information it contains. Presenting the latest developments in complex pattern mining, this book is a valuable reference resource for data science researchers and professionals in academia and industry.
Download or read book Understanding Complex Datasets written by David Skillicorn and published by CRC Press. This book was released on 2007-05-17 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book
Download or read book New Frontiers in Mining Complex Patterns written by Michelangelo Ceci and published by Springer Nature. This book was released on 2020-05-13 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with ECML-PKDD 2019 in Würzburg, Germany, in September 2019. The workshop focused on the latest developments in the analysis of complex and massive data sources, such as blogs, event or log data, medical data, spatio-temporal data, social networks, mobility data, sensor data and streams.
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.
Download or read book Advances in Knowledge Discovery and Data Mining written by Zhi-Hua Zhou and published by Springer Science & Business Media. This book was released on 2007-04-27 with total page 2367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China, May 2007. It covers new ideas, original research results and practical development experiences from all KDD-related areas including data mining, machine learning, data warehousing, data visualization, automatic scientific discovery, knowledge acquisition and knowledge-based systems.
Download or read book New Frontiers in Mining Complex Patterns written by Annalisa Appice and published by Springer. This book was released on 2017-07-01 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 5th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2016, held in conjunction with ECML-PKDD 2016 in Riva del Garda, Italy, in September 2016. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications.
Download or read book Data Mining written by Charu C. Aggarwal and published by Springer. This book was released on 2015-04-13 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples. Praise for Data Mining: The Textbook - “As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology "This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at Chicago
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
Download or read book Successes and New Directions in Data Mining written by Florent Masseglia and published by IGI Global. This book was released on 2008-01-01 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book addresses existing solutions for data mining, with particular emphasis on potential real-world applications. It captures defining research on topics such as fuzzy set theory, clustering algorithms, semi-supervised clustering, modeling and managing data mining patterns, and sequence motif mining"--Provided by publisher.
Download or read book Scientific Data Mining and Knowledge Discovery written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2009-09-19 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mohamed Medhat Gaber “It is not my aim to surprise or shock you – but the simplest way I can summarise is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind has been applied” by Herbert A. Simon (1916-2001) 1Overview This book suits both graduate students and researchers with a focus on discovering knowledge from scienti c data. The use of computational power for data analysis and knowledge discovery in scienti c disciplines has found its roots with the re- lution of high-performance computing systems. Computational science in physics, chemistry, and biology represents the rst step towards automation of data analysis tasks. The rational behind the developmentof computationalscience in different - eas was automating mathematical operations performed in those areas. There was no attention paid to the scienti c discovery process. Automated Scienti c Disc- ery (ASD) [1–3] represents the second natural step. ASD attempted to automate the process of theory discovery supported by studies in philosophy of science and cognitive sciences. Although early research articles have shown great successes, the area has not evolved due to many reasons. The most important reason was the lack of interaction between scientists and the automating systems.
Download or read book New Frontiers in Mining Complex Patterns written by Annalisa Appice and published by Springer. This book was released on 2018-03-27 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 6th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2017, held in conjunction with ECML-PKDD 2017 in Skopje, Macedonia, in September 2017. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications. The workshop was aimed at discussing and introducing new algorithmic foundations and representation formalisms in complex pattern discovery. Finally, it encouraged the integration of recent results from existing fields, such as Statistics, Machine Learning and Big Data Analytics.
Download or read book Data Mining and Analysis written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2014-05-12 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics. This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, algorithmic perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike.
Download or read book Mining Complex Data written by Zbigniew W. Ras and published by Springer Science & Business Media. This book was released on 2008-05-26 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.
Download or read book High Utility Pattern Mining written by Philippe Fournier-Viger and published by Springer. This book was released on 2019-01-18 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data. The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.
Download or read book Symmetry Measures on Complex Networks written by Angel Garrido and published by MDPI. This book was released on 2018-07-09 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Symmetry Measures on Complex Networks" that was published in Symmetry
Download or read book Knowledge Discovery and Data Mining Current Issues and New Applications written by Takao Terano and published by Springer Science & Business Media. This book was released on 2007-07-13 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000) was held at the Keihanna-Plaza, Kyoto, Japan, April 18 - 20, 2000. PAKDD 2000 provided an international forum for researchers and applica tion developers to share their original research results and practical development experiences. A wide range of current KDD topics were covered including ma chine learning, databases, statistics, knowledge acquisition, data visualization, knowledge-based systems, soft computing, and high performance computing. It followed the success of PAKDD 97 in Singapore, PAKDD 98 in Austraha, and PAKDD 99 in China by bringing together participants from universities, indus try, and government from all over the world to exchange problems and challenges and to disseminate the recently developed KDD techniques. This PAKDD 2000 proceedings volume addresses both current issues and novel approaches in regards to theory, methodology, and real world application. The technical sessions were organized according to subtopics such as Data Mining Theory, Feature Selection and Transformation, Clustering, Application of Data Mining, Association Rules, Induction, Text Mining, Web and Graph Mining. Of the 116 worldwide submissions, 33 regular papers and 16 short papers were accepted for presentation at the conference and included in this volume. Each submission was critically reviewed by two to four program committee members based on their relevance, originality, quality, and clarity.
Download or read book Domain Driven Data Mining written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output.
