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Discovery Science, Nathalie Japkowicz; Stan Matwin


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Автор: Nathalie Japkowicz; Stan Matwin
Название:  Discovery Science
ISBN: 9783319242811
Издательство: Springer
Классификация:






ISBN-10: 3319242814
Обложка/Формат: Paperback
Страницы: 342
Вес: 0.50 кг.
Дата издания: 14.09.2015
Серия: Lecture Notes in Artificial Intelligence
Язык: English
Размер: 234 x 156 x 19
Основная тема: Computer Science
Подзаголовок: 18th International Conference, DS 2015, Banff, AB, Canada, October 4-6, 2015. Proceedings
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:

Bilinear Prediction using Low Rank Models.- Finding Hidden Structure in Data with Tensor Decompositions.- Turning Prediction Tools Into Decision Tools.- Overcoming obstacles to the adoption of machine learning by domain Experts.- Resolution transfer in cancer classification based on amplification patterns.- Very Short-Term Wind Speed Forecasting using Spatio-Temporal Lazy Learning.- Discovery of Parameters for Animation of Midge Swarms.- No Sentiment is an Island: Authors activity and sentiments transactions in sentiment classification.- Active Learning for Classifying Template Matches in Historical Maps.- An evaluation of score descriptors combined with non-linear models of expressive dynamics in music.- Geo-Coordinated Parallel Coordinates (GCPC): A Case Study of Environmental Data Analysis.- Generalized Shortest Path Kernel on Graphs.- Ensembles of extremely randomized trees for multi-target regression.- Clustering-Based Optimised Probabilistic Active Learning (COPAL).- Predictive Analysis on Tracking Emails for Targeted Marketing.- Semi-supervised Learning for Stream Recommender Systems.- Detecting Transmembrane Proteins Using Decision Trees.- Change point detection for information diffusion tree.- Multi-label Classification via Multi-target Regression on Data Streams.- Periodical Skeletonization for Partially Periodic Pattern Mining.- Predicting Drugs Adverse Side-Effects using a recommender-system.- Dr. Inventor Framework: extracting structured information from scientific publications.- Predicting Protein Function and Protein-Ligand Interaction with the 3D Neighborhood Kernel.- Hierarchical Multidimensional Classification of web documents with MultiWebClass.- Evaluating the Effectiveness of Hashtags as Predictors of the Sentiment of Tweets.- On the Feasibility of Discovering Meta-Patterns from a Data Ensemble.- An Algorithm for Influence Maximization in a Two-Terminal Series.- Parallel Graph and Its Application to a Real Network.- Benchmarking Stream Clustering for Churn Detection in Dynamic Networks .- Canonical Correlation Methods for Exploring Microbe-Environment Interactions in Deep Subsurface.- KeCo: Kernel-based Online Co-agreement Algorithm.- Tree PCA for Extracting Dominant Substructures from Labeled Rooted Trees.- Enumerating Maximal Clique Sets with Pseudo-Clique Constraint.




Trends and Applications in Knowledge Discovery and Data Mining

Автор: U Kang; Ee-Peng Lim; Jeffrey Xu Yu; Yang-Sae Moon
Название: Trends and Applications in Knowledge Discovery and Data Mining
ISBN: 3319672738 ISBN-13(EAN): 9783319672731
Издательство: Springer
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Цена: 7685.00 р.
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Описание: The workshops affiliated with PAKDD 2017 include: Workshop on Machine Learning for Sensory Data Analysis (MLSDA), Workshop on Biologically Inspired Data Mining Techniques (BDM), Pacific Asia Workshop on Intelligence and Security Informatics (PAISI), and Workshop on Data Mining in Business Process Management (DM-BPM).

Data Mining and Knowledge Discovery for Process Monitoring and Control

Автор: Xue Z. Wang
Название: Data Mining and Knowledge Discovery for Process Monitoring and Control
ISBN: 1447111370 ISBN-13(EAN): 9781447111375
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support.

Data Science, Learning by Latent Structures, and Knowledge Discovery

Автор: Berthold Lausen; Sabine Krolak-Schwerdt; Matthias
Название: Data Science, Learning by Latent Structures, and Knowledge Discovery
ISBN: 366244982X ISBN-13(EAN): 9783662449820
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data;

Advances in Knowledge Discovery and Data Mining

Автор: Jinho Kim; Kyuseok Shim; Longbing Cao; Jae-Gil Lee
Название: Advances in Knowledge Discovery and Data Mining
ISBN: 3319575287 ISBN-13(EAN): 9783319575285
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. spatio-temporal and sequential data mining; dynamic, stream data mining; behavioral data mining;

Advances in Knowledge Discovery and Management

Автор: Bruno Pinaud; Fabrice Guillet; Bruno Cremilleux; C
Название: Advances in Knowledge Discovery and Management
ISBN: 3319654055 ISBN-13(EAN): 9783319654058
Издательство: Springer
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Цена: 16769.00 р.
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Описание:

This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of "Knowledge Discovery and Management" (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories.

The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC'2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.

Discovery Science

Автор: Akihiro Yamamoto; Takuya Kida; Takeaki Uno; Tetsuj
Название: Discovery Science
ISBN: 3319677853 ISBN-13(EAN): 9783319677859
Издательство: Springer
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Цена: 9083.00 р.
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Описание: This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017.

Discriminative Pattern Discovery on Biological Networks

Автор: Fabio Fassetti; Simona E. Rombo; Cristina Serrao
Название: Discriminative Pattern Discovery on Biological Networks
ISBN: 3319634763 ISBN-13(EAN): 9783319634760
Издательство: Springer
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Цена: 7685.00 р.
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Описание:

Part I: Biological Networks

Data Sources and Models

Problems and Techniques

Part II: Pattern Mining

Exceptional Pattern Discovery

Discriminating Graph Pattern Mining from Gene Expression Data

Big Data Analytics and Knowledge Discovery

Автор: Ladjel Bellatreche; Sharma Chakravarthy
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3319642820 ISBN-13(EAN): 9783319642826
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions.

Visual Pattern Discovery and Recognition

Автор: Hongxing Wang; Chaoqun Weng; Junsong Yuan
Название: Visual Pattern Discovery and Recognition
ISBN: 9811048398 ISBN-13(EAN): 9789811048395
Издательство: Springer
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Цена: 7685.00 р.
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Описание: 1. Introduction.- 2. Context-Aware Discovery of Visual Co-occurrence Patterns.- 3. Hierarchical Sparse Coding for Visual Co-occurrence Discovery.- 4. Feature Co-occurrence for Visual Labeling.- 5. Visual Clustering with Minimax Feature Fusion.- 6. Conclusion.

Soft Computing for Knowledge Discovery

Автор: James G. Shanahan
Название: Soft Computing for Knowledge Discovery
ISBN: 0792379187 ISBN-13(EAN): 9780792379188
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Knowledge discovery is an area of computer science that attempts to uncover interesting patterns in data that permit a computer to perform a task autonomously. This title provides a self-contained exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspective.


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