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Author: Dinesh P. Mehta
Publisher: Taylor & Francis
ISBN: 1498701884
Category : Computers
Languages : en
Pages : 1121
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Book Description
The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook 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. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for 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.
Author: Dinesh P. Mehta
Publisher: Taylor & Francis
ISBN: 1498701884
Category : Computers
Languages : en
Pages : 1121
Get Book Here
Book Description
The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook 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. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for 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.
Author: Maria E. Orlowska
Publisher: Springer Science & Business Media
ISBN: 1447115252
Category : Computers
Languages : en
Pages : 514
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Book Description
The papers published here highlight the contributions of leading researchers in the field who are working with object-oriented technology, theory and practice. Among the topics to be covered are: object-relational data technology; distributed object computing; patterns and frameworks; concepts and methodologies; multimedia systems; object-0riented metrics; object reuse; object ontologies; business process re-design; knowledge management; object database management systems; and interoperability issues. Areas of significant interest to industry, especially in providing innovative directions for the development of next generation systems, are also covered.
Author: Herman Rubin
Publisher: IMS
ISBN: 9780940600614
Category : Bayesian statistical decision theory
Languages : en
Pages : 442
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Book Description
Author: Erickson, John
Publisher: IGI Global
ISBN: 1605660590
Category : Business & Economics
Languages : en
Pages : 2780
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Book Description
"This reference expands the field of database technologies through four-volumes of in-depth, advanced research articles from nearly 300 of the world's leading professionals"--Provided by publisher.
Author: Florent Masseglia
Publisher: IGI Global
ISBN: 1599046458
Category : Computers
Languages : en
Pages : 386
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Book Description
"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.
Author: Lingyu Wang
Publisher: Springer Science & Business Media
ISBN: 0387462740
Category : Computers
Languages : en
Pages : 180
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Book Description
This book addresses the privacy issue of On-Line Analytic Processing (OLAP) systems. OLAP systems usually need to meet two conflicting goals. First, the sensitive data stored in underlying data warehouses must be kept secret. Second, analytical queries about the data must be allowed for decision support purposes. The main challenge is that sensitive data can be inferred from answers to seemingly innocent aggregations of the data. This volume reviews a series of methods that can precisely answer data cube-style OLAP, regarding sensitive data while provably preventing adversaries from inferring data.
Author: Viviana E. Ferraggine
Publisher: IGI Global
ISBN: 1605662437
Category : Computers
Languages : en
Pages : 1050
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Book Description
"This book provides a wide compendium of references to topics in the field of the databases systems and applications"--Provided by publisher.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1466624566
Category : Computers
Languages : en
Pages : 2335
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Book Description
Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.
Author: Junjie Wu
Publisher: Springer Science & Business Media
ISBN: 3642298079
Category : Computers
Languages : en
Pages : 187
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Book Description
Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.
Author: Chengqi Zhang
Publisher: Springer
ISBN: 3540460276
Category : Computers
Languages : en
Pages : 247
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Book Description
Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.
