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Nearest Neighbor Search:

Author: Apostolos N. Papadopoulos

Publisher: Springer Science & Business Media

Published: 2006-11-22

Total Pages: 179

ISBN-13: 0387275444

Modern applications are both data and computationally intensive and require the storage and manipulation of voluminous traditional (alphanumeric) and nontraditional data sets (images, text, geometric objects, time-series). Examples of such emerging application domains are: Geographical Information Systems (GIS), Multimedia Information Systems, CAD/CAM, Time-Series Analysis, Medical Information Sstems, On-Line Analytical Processing (OLAP), and Data Mining. These applications pose diverse requirements with respect to the information and the operations that need to be supported. From the database perspective, new techniques and tools therefore need to be developed towards increased processing efficiency. This monograph explores the way spatial database management systems aim at supporting queries that involve the space characteristics of the underlying data, and discusses query processing techniques for nearest neighbor queries. It provides both basic concepts and state-of-the-art results in spatial databases and parallel processing research, and studies numerous applications of nearest neighbor queries.

Nearest Neighbor Search:

Author: Apostolos N. Papadopoulos

Publisher: Springer Science & Business Media

Published: 2005

Total Pages: 200

ISBN-13: 9780387229638

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Explores the way spatial database management systems aim at supporting queries that involve the space characteristics of the underlying data. This book discusses query processing techniques for nearest neighbor queries. It provides both basic concepts and results in spatial databases and parallel processing research.

Nearest Neighbor Search:

Author: Apostolos N. Papadopoulos

Publisher: Springer

Published: 2010-12-06

Total Pages: 0

ISBN-13: 9781441935649

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Dimensionality Reduction with Unsupervised Nearest Neighbors

Author: Oliver Kramer

Publisher: Springer Science & Business Media

Published: 2013-05-30

Total Pages: 137

ISBN-13: 3642386520

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This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustrate the introduced concepts and to highlight the experimental results.

Advances in Spatial and Temporal Databases

Author: Christian S. Jensen

Publisher: Springer Science & Business Media

Published: 2001-07-02

Total Pages: 532

ISBN-13: 354042301X

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This book constitutes the refereed proceedings of the 7th International Conference on Spatial and Temporal Databases, SSTD 2001, held in Redondo Beach, CA, USA, in July 2001. The 25 revised full papers and two industrial papers presented were carefully reviewed and selected from a total of 70 submissions. The book offers topical sections on modeling and querying, moving-object query processing, query processing: architectures and cost estimation, processing advanced queries, formal aspects, data representation, industrial session, data warehousing and mining, and indexing.

Lectures on the Nearest Neighbor Method

Author: Gérard Biau

Publisher: Springer

Published: 2015-12-08

Total Pages: 290

ISBN-13: 3319253883

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This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).

LATIN 2008: Theoretical Informatics

Author: Eduardo Sany Laber

Publisher: Springer Science & Business Media

Published: 2008-03-17

Total Pages: 808

ISBN-13: 3540787720

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This book constitutes the refereed proceedings of the 8th International Latin American Symposium on Theoretical Informatics, LATIN 2008, held in Búzios, Brazil, in April 2008. The 66 revised full papers presented together with the extended abstract of 1 invited paper were carefully reviewed and selected from 242 submissions. The papers address a veriety of topics in theoretical computer science with a certain focus on algorithms, automata theory and formal languages, coding theory and data compression, algorithmic graph theory and combinatorics, complexity theory, computational algebra, computational biology, computational geometry, computational number theory, cryptography, theoretical aspects of databases and information retrieval, data structures, networks, logic in computer science, machine learning, mathematical programming, parallel and distributed computing, pattern matching, quantum computing and random structures.

Computer Vision Systems

Author: Mario Fritz

Publisher: Springer

Published: 2009-10-14

Total Pages: 468

ISBN-13: 3642046673

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This book constitutes the refereed proceedings of the 7th International Conference on Computer Vision Systems, ICVS 2009, held in Liege, Belgium, October 13-15, 2009. The 21 papers for oral presentation presented together with 24 poster presentations and 2 invited papers were carefully reviewed and selected from 96 submissions. The papers are organized in topical sections on human-machine-interaction, sensors, features and representations, stereo, 3D and optical flow, calibration and registration, mobile and autonomous systems, evaluation, studies and applications, learning, recognition and adaption.

Algorithms and Data Structures

Author: Frank Dehne

Publisher: Springer

Published: 2007-08-21

Total Pages: 664

ISBN-13: 3540739513

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This book constitutes the refereed proceedings of the 10th International Workshop on Algorithms and Data Structures, WADS 2007, held in Halifax, Canada, in August 2007. The papers present original research on the theory and application of algorithms and data structures in all areas, including combinatorics, computational geometry, databases, graphics, parallel and distributed computing.

Data Algorithms

Author: Mahmoud Parsian

Publisher: "O'Reilly Media, Inc."

Published: 2015-07-13

Total Pages: 778

ISBN-13: 1491906154

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If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. Topics include: Market basket analysis for a large set of transactions Data mining algorithms (K-means, KNN, and Naive Bayes) Using huge genomic data to sequence DNA and RNA Naive Bayes theorem and Markov chains for data and market prediction Recommendation algorithms and pairwise document similarity Linear regression, Cox regression, and Pearson correlation Allelic frequency and mining DNA Social network analysis (recommendation systems, counting triangles, sentiment analysis)