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Engineering Compact Dynamic Data Structures And In Memory Data Mining
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Book Synopsis Algorithms and Data Structures for External Memory by : Jeffrey Scott Vitter
Download or read book Algorithms and Data Structures for External Memory written by Jeffrey Scott Vitter and published by Now Publishers Inc. This book was released on 2008 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.
Book Synopsis Dynamic and Advanced Data Mining for Progressing Technological Development: Innovations and Systemic Approaches by : Ali, A B M Shawkat
Download or read book Dynamic and Advanced Data Mining for Progressing Technological Development: Innovations and Systemic Approaches written by Ali, A B M Shawkat and published by IGI Global. This book was released on 2009-11-30 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book discusses advances in modern data mining research in today's rapidly growing global and technological environment"--Provided by publisher.
Book Synopsis Proceedings of the Sixth SIAM International Conference on Data Mining by : Joydeep Ghosh
Download or read book Proceedings of the Sixth SIAM International Conference on Data Mining written by Joydeep Ghosh and published by SIAM. This book was released on 2006-04-01 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, based on sound statistical foundations. These techniques in turn require powerful visualization technologies; implementations that must be carefully tuned for performance; software systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them.
Book Synopsis Intelligent Computing & Optimization by : Pandian Vasant
Download or read book Intelligent Computing & Optimization written by Pandian Vasant and published by Springer Nature. This book was released on 2021-12-30 with total page 1020 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the scientific results of the fourth edition of the International Conference on Intelligent Computing and Optimization which took place at December 30–31, 2021, via ZOOM. The conference objective was to celebrate “Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization worldwide, to share knowledge, experience, innovation—marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings encloses the original and innovative scientific fields of optimization and optimal control, renewable energy and sustainability, artificial intelligence and operational research, economics and management, smart cities and rural planning, meta-heuristics and big data analytics, cyber security and blockchains, IoTs and Industry 4.0, mathematical modelling and simulation, health care and medicine.
Book Synopsis Handbook of Data Structures and Applications by : Dinesh P. Mehta
Download or read book Handbook of Data Structures and Applications written by Dinesh P. Mehta and published by CRC Press. This book was released on 2004-10-28 with total page 1387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are many advanced and specialized texts and handbooks on algorithms, until now there was no book that focused exclusively on the wide variety of data structures that have been reported in the literature. The Handbook of Data Structures and Applications responds to the needs of students, professionals, and researchers who need a mainstream reference on data structures by providing a comprehensive survey of data structures of various types. Divided into seven parts, the text begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. The Handbook is invaluable in suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
Book Synopsis Computational Intelligence and Intelligent Systems by : Zhenhua Li
Download or read book Computational Intelligence and Intelligent Systems written by Zhenhua Li and published by Springer. This book was released on 2012-10-06 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Symposium on Intelligence Computation and Applications, ISICA 2012, held in Wuhan, China, in October 2012. The 72 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; combinatorial and numerical optimization; communications and computer networks; data mining; evolutionary multi-objective and dynamic optimization; intelligent computation, intelligent learning systems; neural networks; real-world applications.
Book Synopsis Data Mining for Scientific and Engineering Applications by : R.L. Grossman
Download or read book Data Mining for Scientific and Engineering Applications written by R.L. Grossman and published by Springer Science & Business Media. This book was released on 2001-10-31 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.
Book Synopsis Intelligent Data Engineering and Automated Learning by : Jiming Liu
Download or read book Intelligent Data Engineering and Automated Learning written by Jiming Liu and published by Springer Science & Business Media. This book was released on 2003-07-29 with total page 1161 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the throughly refereed post-proceedings of the 4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003, held in Hong Kong, China in March 2003. The 164 revised papers presented were carefully reviewed and selected from 321 submissions; for inclusion in this post-proceedings another round of revision was imposed. The papers are organized in topical sections an agents, automated learning, bioinformatics, data mining, multimedia information, and financial engineering.
Book Synopsis Algorithm Engineering and Experimentation by : Michael T. Goodrich
Download or read book Algorithm Engineering and Experimentation written by Michael T. Goodrich and published by Springer Science & Business Media. This book was released on 1999-06-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Algorithmic Engineering and Experimentation, ALENEX'99, held in Baltimore, Maryland, USA, in January 1999. The 20 revised full papers presented were carefully selected from a total of 42 submissions during two rounds of reviewing and improvement. The papers are organized in sections on combinatorial algorithms, computational geometry, software and applications, algorithms for NP-hard problems, and data structures.
Book Synopsis Advances in Knowledge Discovery and Data Mining by : Takashi Washio
Download or read book Advances in Knowledge Discovery and Data Mining written by Takashi Washio and published by Springer Science & Business Media. This book was released on 2008-05-08 with total page 1125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008, held in Osaka, Japan, in May 2008. The 37 revised long papers, 40 revised full papers, and 36 revised short papers presented together with 1 keynote talk and 4 invited lectures were carefully reviewed and selected from 312 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.
Book Synopsis String Processing and Information Retrieval by : Liliana Calderon-Benavides
Download or read book String Processing and Information Retrieval written by Liliana Calderon-Benavides and published by Springer. This book was released on 2012-09-13 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Symposium on String Processing and Information Retrieval, SPIRE 2012, held in Cartagena de Indias, Colombia, in October 2012. The 26 full papers, 13 short papers, and 3 keynote speeches were carefully reviewed and selected from 81 submissions. The following topics are covered: fundamentals algorithms in string processing and information retrieval; SP and IR techniques as applied to areas such as computational biology, DNA sequencing, and Web mining.
Book Synopsis Intelligent Data Engineering and Automated Learning - IDEAL 2005 by : Marcus Gallagher
Download or read book Intelligent Data Engineering and Automated Learning - IDEAL 2005 written by Marcus Gallagher and published by Springer. This book was released on 2005-06-20 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume in the Lecture Notes in Computer Science series contains accepted papers presented at IDEAL 2005, held in Brisbane, Australia, during July 6–8, 2005.
Download or read book Data Streams written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2007-04-03 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.
Book Synopsis Proceedings of the Seventh SIAM International Conference on Data Mining by : Chid Apte
Download or read book Proceedings of the Seventh SIAM International Conference on Data Mining written by Chid Apte and published by Proceedings in Applied Mathema. This book was released on 2007 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question.
Book Synopsis Principles of Data Mining by : David J. Hand
Download or read book Principles of Data Mining written by David J. Hand and published by MIT Press. This book was released on 2001-08-17 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
Book Synopsis Modeling Decisions for Artificial Intelligence by : Vincenc Torra
Download or read book Modeling Decisions for Artificial Intelligence written by Vincenc Torra and published by Springer. This book was released on 2012-11-07 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2012, held in Girona, Catalonia, Spain, in November 2012. The 32 revised full papers were carefully reviewed and selected from 49 submissions and are presented with 4 plenary talks. The papers are organized in topical sections on aggregation operators, integrals, data privacy and security, reasoning, applications, and clustering and similarity.
Book Synopsis High-Utility Pattern Mining by : Philippe Fournier-Viger
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 343 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.
