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الصفحة 2
الصفحة 2
Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Algorithms and data structures : The Basic Toolbox
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language.
Algorithms – ESA 2007 ; 15th Annual European Symposium, Eilat, Israel, October 8-10, 2007, Proceedings
This book presented submissions in the engineering and applications track. The papers address all current subjects in algorithmics reaching from design and analysis issues of algorithms over to real-world applicat.
Algorithms – ESA 2005 ; 13th Annual European Symposium, Palma de Mallorca, Spain, October 3-6, 2005, Proceedings
This volume contains the 75 contributed papers and the abstracts of the threeinvited lectures presented at the 13th Annual European Symposium on Algo-rithms (ESA 2005), held in Spain, 2005. respectively.Papers were solicited in all areas of algorithmic research, including but notlimited to algorithmic aspects of networks, approximation and on-line algo-rithms, computational biology, computational geometry, computational financeand algorithmic game theory, data structures, database and information re-trieval, external memory algorithms, graph algorithms, graph drawing, machinelearning, mobile computing, pattern matching and data compression, quantumcomputing, and randomized algorithms. The algorithms could be sequential,distributed, or parallel. Submissions were especially encouraged in the area ofmathematical programming and operations research, including combinatorialoptimization, integer programming, polyhedral combinatorics, and semidefiniteprogramming.Each extended abstract was submitted to one of the two tracks.
Advanced Data Warehouse Design : From Conventional to Spatial and Temporal Applications
This book serves as an introduction to the state of the art on data warehouse design, with many references to more detailed sources. Providing a clear and a concise presentation of the major concepts and results of data warehouse design, it can also be used as the basis of a graduate or advanced undergraduate course.
Advanced Algorithms and Data Structures
introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms
A Modular Calculus for the Average Cost of Data Structuring
This volume, with forewords by Greg Bollella and Dana Scott, presents novel programs based on the new advances in this area, including the first randomness-preserving version of Heapsort. Programs are provided, along with derivations of their average-case time, to illustrate the radically different approach to average-case timing. The automated static timing tool applies the Modular Calculus to extract the average-case running time of programs directly from their MOQA code.
3D Mesh processing and character animation : with examples using OpenGL, OpenMesh and Assimp
Focusses specifically on topics that are important in three-dimensional modelling, surface design and real-time character animation. It provides an in-depth coverage of data structures and popular methods used in geometry processing, keyframe and inverse kinematics animations and shader based processing of mesh objects. It also introduces two powerful and versatile libraries, OpenMesh and Assimp, and demonstrates their usefulness through implementations of a wide range of algorithms in mesh processing and character animation respectively. This Textbook is written for students at an advanced undergraduate or postgraduate level who are interested in the study and development of graphics algorithms for three-dimensional mesh modeling and analysis, and animations of rigged character models.
Making with data : Physical design and craft in a data-driven world
Making with Data: Physical Design and Craft in a Data-Driven World provides a snapshot of the diverse practices contemporary creators are using to produce objects, spaces, and experiences imbued with data. Across 25+ beautifully-illustrated chapters, international artists, designers, and scientists each explain the process of creating a specific data-driven piece—illustrating their practice with candid sketches, photos, and design artifacts from their own studios. Featuring influential voices in computer science, data science, graphic design, art, craft, and architecture, Making with Data is accessible and inspiring for enthusiasts and experts alike.
Adaptive Atmospheric Modeling : Key Techniques in Grid Generation, Data Structures, and Numerical Operations with Applications
This is an overview of the development of adaptive techniques for atmospheric modeling. Written in an educational style, it functions as a starting point for readers interested in adaptive modeling, in atmospheric sciences and beyond. Coverage includes paradigms of adaptive techniques, such as error estimation and adaptation criteria. Mesh generation methods are presented for triangular/tetrahedral and quadrilateral/hexahedral meshes, with a special section on initial meshes for the sphere.
