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Multidimensional Mining of Massive Text Data, Zhang, Chao Han, Jiawei


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Автор: Zhang, Chao Han, Jiawei
Название:  Multidimensional Mining of Massive Text Data
ISBN: 9783031007866
Издательство: Springer
Классификация:


ISBN-10: 3031007867
Обложка/Формат: Paperback
Страницы: 183
Вес: 0.39 кг.
Дата издания: 21.03.2019
Серия: Synthesis lectures on data mining and knowledge discovery
Язык: English
Иллюстрации: Xiii, 183 p.
Размер: 189 x 234 x 14
Ссылка на Издательство: Link
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Поставляется из: Германии


Mining of Massive Datasets

Автор: Leskovec Jure
Название: Mining of Massive Datasets
ISBN: 1108476341 ISBN-13(EAN): 9781108476348
Издательство: Cambridge Academ
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Цена: 10771.00 р.
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Описание: Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Knowledge Discovery and Data Mining

Автор: O. Maimon; M. Last
Название: Knowledge Discovery and Data Mining
ISBN: 1441948422 ISBN-13(EAN): 9781441948427
Издательство: Springer
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Цена: 17069.00 р.
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Описание: This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http: //www.eng.tau.ac.iV-maimonlifn-kdg ). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).

Massive graph analytics /

Автор: David A. Bader
Название: Massive graph analytics /
ISBN: 0367464128 ISBN-13(EAN): 9780367464127
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: Massive Graph Analytics provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. The book will be beneficial to students, researchers and practitioners, in academia, national laboratories, and industry in massive scale graph analytics.

Grouping Multidimensional Data

Автор: Jacob Kogan; Charles Nicholas; Marc Teboulle
Название: Grouping Multidimensional Data
ISBN: 3642066542 ISBN-13(EAN): 9783642066542
Издательство: Springer
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Цена: 15855.00 р.
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Описание: Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data.

Machine Learning for Text

Автор: Charu C. Aggarwal
Название: Machine Learning for Text
ISBN: 3030088073 ISBN-13(EAN): 9783030088071
Издательство: Springer
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Цена: 6097.00 р.
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Описание: Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories:- Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for machine learning from text such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.- Domain-sensitive mining: Chapters 8 and 9 discuss the learning methods from text when combined with different domains such as multimedia and the Web. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. - Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This textbook covers machine learning topics for text in detail. Since the coverage is extensive,multiple courses can be offered from the same book, depending on course level. Even though the presentation is text-centric, Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offer courses not just in text analytics but also from the broader perspective of machine learning (with text as a backdrop). This textbook targets graduate students in computer science, as well as researchers, professors, and industrial practitioners working in these related fields. This textbook is accompanied with a solution manual for classroom teaching.

Text Mining

Автор: Ashok N. Srivastava, Mehran Sahami
Название: Text Mining
ISBN: 1420059408 ISBN-13(EAN): 9781420059403
Издательство: Taylor&Francis
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Цена: 16078.00 р.
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Описание: Focuses on statistical methods for text mining and analysis. This work examines methods to automatically cluster and classify text documents and applies these methods in a variety of areas, including adaptive information filtering, information distillation, and text search.

Fuzzy Set Approach to Multidimensional Poverty Measurement

Автор: Achille A. Lemmi; Gianni Betti
Название: Fuzzy Set Approach to Multidimensional Poverty Measurement
ISBN: 1441941711 ISBN-13(EAN): 9781441941718
Издательство: Springer
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Цена: 20733.00 р.
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Описание: This volume brings together advanced thinking on the multidimensional measurement of poverty.

Statistical Image Processing and Multidimensional Modeling

Автор: Paul Fieguth
Название: Statistical Image Processing and Multidimensional Modeling
ISBN: 1461427053 ISBN-13(EAN): 9781461427056
Издательство: Springer
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Цена: 15855.00 р.
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Описание: Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media).

Decision Space: Multidimensional Utility Analysis

Автор: Weirich Paul
Название: Decision Space: Multidimensional Utility Analysis
ISBN: 0521800099 ISBN-13(EAN): 9780521800099
Издательство: Cambridge Academ
Цена: 15206.00 р.
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Описание: In Decision Space: Multidimensional Utility Analysis, first published in 2001, Paul Weirich increases the power and versatility of utility analysis and in the process advances decision theory. Combining traditional and novel methods of option evaluation into one systematic method, multidimensional utility analysis is a valuable tool in decision theory.

Multidimensional Similarity Structure Analysis

Автор: I. Borg; J. Lingoes
Название: Multidimensional Similarity Structure Analysis
ISBN: 146129147X ISBN-13(EAN): 9781461291473
Издательство: Springer
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Цена: 12805.00 р.
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Описание: Multidimensional Similarity Structure Analysis comprises a class of models that represent similarity among entities (for example, variables, items, objects, persons, etc.) in multidimensional space to permit one to grasp more easily the interrelations and patterns present in the data.

Applied multidimensional scaling and unfolding.

Автор: Ingwer Borg, Patrick J.F. Groenen, Patrick Mair
Название: Applied multidimensional scaling and unfolding.
ISBN: 3319734709 ISBN-13(EAN): 9783319734705
Издательство: Springer
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Цена: 7927.00 р.
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Описание: This book introduces multidimensional scaling (MDS) and unfolding as data analysis techniques for applied researchers. Unfolding is a related method that maps preference data (typically evaluative ratings of different persons on a set of objects) as distances between two sets of points (representing the persons and the objects, resp.).

Kronecker Modeling and Analysis of Multidimensional Markovian Systems

Автор: Tu?rul Dayar
Название: Kronecker Modeling and Analysis of Multidimensional Markovian Systems
ISBN: 331997128X ISBN-13(EAN): 9783319971285
Издательство: Springer
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Цена: 12196.00 р.
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Описание: This work considers Kronecker-based models with finite as well as countably infinite state spaces for multidimensional Markovian systems by paying particular attention to those whose reachable state spaces are smaller than their product state spaces. Numerical methods for steady-state and transient analysis of Kronecker-based multidimensional Markovian models are discussed in detail together with implementation issues. Case studies are provided to explain concepts and motivate use of methods. Having grown out of research from the past twenty years, this book expands upon the author’s previously published book Analyzing Markov Chains using Kronecker Products (Springer, 2012). The subject matter is interdisciplinary and at the intersection of applied mathematics and computer science. The book will be of use to researchers and graduate students with an understanding of basic linear algebra, probability, and discrete mathematics.


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