Efficient Frequent Pattern Mining From Big Data And Its Applications
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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.
Efficient Frequent Pattern Mining From Big Data And Its Applications
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Author : Fan Jiang
language : en
Publisher:
Release Date : 2014
Efficient Frequent Pattern Mining From Big Data And Its Applications written by Fan Jiang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Frequent pattern mining is an important research areas in data mining. Since its introduction, it has drawn attention of many researchers. Consequently, many algorithms have been proposed. Popular algorithms include level-wise Apriori based algorithms, tree based algorithms, and hyperlinked array structure based algorithms. While these algorithms are popular and beneficial due to some nice properties, they also suffer from some drawbacks such as multiple database scans, recursive tree constructions, or multiple hyperlink adjustments. In the current era of big data, high volumes of a wide variety of valuable data of different veracities can be easily collected or generated at high velocity in various real-life applications. Among these 5V's of big data, I focus on handling high volumes of big data in my Ph.D. thesis. Specifically, I design and implement a new efficient frequent pattern mining algorithmic technique called B-mine, which overcomes some of the aforementioned drawbacks and achieves better performance when compared with existing algorithms. I also extend my B-mine algorithm into a family of algorithms that can perform big data mining efficiently. Moreover, I design four different frameworks that apply this family of algorithms to the real-life application of social network mining. Evaluation results show the efficiency and practicality of all these algorithms.
High Utility Pattern Mining
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Author : Philippe Fournier-Viger
language : en
Publisher: Springer
Release Date : 2019-01-18
High Utility Pattern Mining written by Philippe Fournier-Viger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-18 with Computers categories.
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.
Managing And Mining Graph Data
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2012-04-06
Managing And Mining Graph Data 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 2012-04-06 with Computers categories.
Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.
Big Data Applications And Services 2017
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Author : Wookey Lee
language : en
Publisher: Springer
Release Date : 2018-08-16
Big Data Applications And Services 2017 written by Wookey Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-16 with Technology & Engineering categories.
This proceedings volume contains selected papers from the Fourth International Conference on Big Data Applications and Services (BigDAS 2017), held in Tashkent, Uzbekistan on August 15-18, 2017. Big data has become a core technology providing innovative solutions in many fields including social media, healthcare and manufacturing. The Fourth International Conference on Big Data Applications and Services (BigDAS 2017) presented innovative results, encouraged academic and industrial interaction, and promoted collaborative research in the field of big data worldwide. The conference was organized by the Korea Big Data Services Society and National University of Uzbekistan.
Computational Science And Its Applications Iccsa 2018
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Author : Osvaldo Gervasi
language : en
Publisher: Springer
Release Date : 2018-07-03
Computational Science And Its Applications Iccsa 2018 written by Osvaldo Gervasi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-03 with Computers categories.
The five volume set LNCS 10960 until 10964 constitutes the refereed proceedings of the 18th International Conference on Computational Science and Its Applications, ICCSA 2018, held in Melbourne, Australia, in July 2018. Apart from the general tracks, ICCSA 2018 also includes 34 international workshops in various areas of computational sciences, ranging from computational science technologies, to specific areas of computational sciences, such as computer graphics and virtual reality. The total of 265 full papers and 10 short papers presented in the 5-volume proceedings set of ICCSA 2018, were carefully reviewed and selected from 892 submissions. The paper Nitrogen Gas on Graphene: Pairwise Interaction Potentials is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Proceedings Of First International Conference On Smart System Innovations And Computing
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Author : Arun K. Somani
language : en
Publisher: Springer
Release Date : 2018-01-08
Proceedings Of First International Conference On Smart System Innovations And Computing written by Arun K. Somani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-08 with Technology & Engineering categories.
The edited volume contains original papers contributed to 1st International Conference on Smart System, Innovations and Computing (SSIC 2017) by researchers from different countries. The contributions focuses on two main areas, i.e. Smart Systems Innovations which includes applications for smart cities, smart grid, social computing and privacy challenges with their theory, specification, design, performance, and system building. And second Computing of Complex Solutions which includes algorithms, security solutions, communication and networking approaches. The volume provides a snapshot of current progress in related areas and a glimpse of future possibilities. This volume is useful for researchers, Ph.D. students, and professionals working in the core areas of smart systems, innovations and computing.
Big Data
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Author : Rob Botwright
language : en
Publisher: Rob Botwright
Release Date : 2024
Big Data written by Rob Botwright and has been published by Rob Botwright this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Computers categories.
Uncover the secrets of Big Data with our comprehensive book bundle: "Big Data: Statistics, Data Mining, Analytics, and Pattern Learning." Dive into the world of data analytics and processing with Book 1, where you'll gain a solid understanding of the fundamentals necessary to navigate the vast landscape of big data. In Book 2, explore data mining techniques that allow you to extract valuable insights and patterns from large datasets. From marketing to finance and beyond, discover how to uncover hidden trends that drive informed decision-making. Ready to take your skills to the next level? Book 3 delves into advanced data science, where you'll learn to harness the power of machine learning for big data analysis. From regression analysis to neural networks, master the tools and techniques that drive predictive modeling and pattern recognition. Finally, in Book 4, learn how to design robust big data architectures that can scale to meet the needs of modern enterprises. Explore architectural patterns, scalability techniques, and fault tolerance mechanisms that ensure your systems are resilient and reliable. Whether you're a beginner looking to build a solid foundation or an experienced professional seeking to deepen your expertise, this book bundle has something for everyone. Don't miss out on this opportunity to unlock the potential of Big Data and drive innovation in your organization. Order now and embark on your journey to becoming a Big Data expert!
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.
Data Warehousing And Mining Concepts Methodologies Tools And Applications
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2008-05-31
Data Warehousing And Mining Concepts Methodologies Tools And Applications written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-31 with Technology & Engineering categories.
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.