Data Mining Patterns
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Foundations Of Data Mining And Knowledge Discovery
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Author : Tsau Young Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-09-02
Foundations Of Data Mining And Knowledge Discovery written by Tsau Young Lin 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 2005-09-02 with Computers categories.
"Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.
Data Mining The Web
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Author : Zdravko Markov
language : en
Publisher: John Wiley & Sons
Release Date : 2007-04-25
Data Mining The Web written by Zdravko Markov and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-25 with Computers categories.
This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).
Complex Pattern Mining
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Author : Annalisa Appice
language : en
Publisher: Springer Nature
Release Date : 2020-01-14
Complex Pattern Mining written by Annalisa Appice and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-14 with Technology & Engineering categories.
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.
Frequent Pattern Mining
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2014-08-29
Frequent Pattern Mining written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-29 with Computers categories.
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.
Mining Sequential Patterns From Large Data Sets
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Author : Wei Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-02-28
Mining Sequential Patterns From Large Data Sets written by Wei Wang 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 2005-02-28 with Computers categories.
In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.
Machine Learning And Data Mining In Pattern Recognition
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2012-07-02
Machine Learning And Data Mining In Pattern Recognition written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-02 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Conference, MLDM 2012, held in Berlin, Germany in July 2012. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.
Data Analysis And Pattern Recognition In Multiple Databases
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Author : Animesh Adhikari
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-09
Data Analysis And Pattern Recognition In Multiple Databases written by Animesh Adhikari 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 2013-12-09 with Technology & Engineering categories.
Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.
Machine Learning And Data Mining In Pattern Recognition
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2018-07-09
Machine Learning And Data Mining In Pattern Recognition written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-09 with Computers categories.
This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Periodic Pattern Mining
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Author : R. Uday Kiran
language : en
Publisher: Springer Nature
Release Date : 2021-10-29
Periodic Pattern Mining written by R. Uday Kiran and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-29 with Computers categories.
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.
Machine Interpretation Of Patterns
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Author : Rajat K. De
language : en
Publisher: World Scientific
Release Date : 2010
Machine Interpretation Of Patterns written by Rajat K. De and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
1. Combining information with a Bayesian multi-class multi-kernel pattern recognition machine / T. Damoulas and M.A. Girolami -- 2. Image quality assessment based on weighted perceptual features / D.V. Rao and L.P. Reddy -- 3. Quasi-reversible two-dimension fractional differentiation for image entropy reduction / A. Nakib [und weitere] -- 4. Parallel genetic algorithm based clustering for object and background classification / P. Kanungo, P.K. Nanda and A. Ghosh -- 5. Bipolar fuzzy spatial information : first operations in the mathematical morphology setting / I. Bloch -- 6. Approaches to intelligent information retrieval / G. Pasi -- 7. Retrieval of on-line signatures / H.N. Prakash and D.S. Guru -- 8. A two stage recognition scheme for offline handwritten Devanagari Words / B. Shaw and S.K. Parui -- 9. Fall detection from a video in the presence of multiple persons / V. Vishwakarma, S. Sural and C. Mandal -- 10. Fusion of GIS and SAR statistical features for earthquake damage mapping at the block scale / G. Trianni [und weitere] -- 11. Intelligent surveillance and Pose-invariant 2D face classification / B.C. Lovell, C. Sanderson and T. Shan -- 12. Simple machine learning approaches to safety-related systems / C. Moewes, C. Otte and R. Kruse -- 13. Nonuniform multi level crossings for signal reconstruction / N. Poojary, H. Kumar and A. Rao -- 14. Adaptive web services brokering / K.M. Gupta and D.W. Aha -- 15. Granular support vector machine based method for prediction of solubility of proteins on over expression in Escherichia Coli and breast cancer classification / P. Kumar, B.D. Kulkarni and V.K. Jayaraman