Developments in Data Extraction, Management, and Analysis, Nhung Do, J. Wenny Rahayu, Torab Torabi

Автор: Kalita
Название: Recent Developments in Machine Learning and Data Analytics
ISBN: 9811312796 ISBN-13(EAN): 9789811312793
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book presents high-quality papers from an international forum for research on computational approaches to learning. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted.

Автор: Ferrari Alberto, Russo Marco
Название: The Definitive Guide to Dax: Business Intelligence for SQL Server Analysis Services and Excel
ISBN: 073569835X ISBN-13(EAN): 9780735698352
Издательство: Неизвестно
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Цена: 57470.00 T
Наличие на складе: Невозможна поставка.
Описание: This comprehensive and authoritative guide will teach you the DAX language for business intelligence, data modeling, and analytics. Leading Microsoft BI consultants Marco Russo and Alberto Ferrari help you master everything from table functions through advanced code and model optimization. You'll learn exactly what happens under the hood when you run a DAX expression, how DAX behaves differently from other languages, and how to use this knowledge to write fast, robust code. If you want to leverage all of DAX's remarkable power and flexibility, this no-compromise "deep dive" is exactly what you need.

Perform powerful data analysis with DAX for Microsoft SQL Server Analysis Services, Excel, and Power BI

• Master core DAX concepts, including calculated columns, measures, and error handling
• Understand evaluation contexts and the CALCULATE and CALCULATETABLE functions
• Perform time-based calculations: YTD, MTD, previous year, working days, and more
• Work with expanded tables, complex functions, and elaborate DAX expressions
• Perform calculations over hierarchies, including parent/child hierarchies
• Use DAX to express diverse and unusual relationships
• Measure DAX query performance with SQL Server Profiler and DAX Studio

Автор: Ahmed
Название: Big and Complex Data Analysis
ISBN: 3319415727 ISBN-13(EAN): 9783319415727
Издательство: Springer
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Цена: 102480.00 T
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Описание: This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data.

Автор: Shalin Hai-Jew
Название: Social Media Data Extraction and Content Analysis
ISBN: 1522506489 ISBN-13(EAN): 9781522506485
Издательство: Mare Nostrum (Eurospan)
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Цена: 222690.00 T
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Описание: Explores various social networking platforms and the technologies being utilized to gather and analyse information being posted to these venues. Highlighting emergent research, analytical techniques, and best practices in data extraction in global electronic culture, this publication is an essential reference source for researchers, academics, and professionals.

Автор: Basant Agarwal; Namita Mittal
Название: Prominent Feature Extraction for Sentiment Analysis
ISBN: 3319253417 ISBN-13(EAN): 9783319253411
Издательство: Springer
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Цена: 121890.00 T
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Описание:

1 Introduction

2 Literature Survey

3 Machine Learning Approach for Sentiment Analysis

4 Semantic Parsing using Dependency Rules

5 Sentiment Analysis using ConceptNet Ontology and Context

Information

6 Semantic Orientation based Approach for Sentiment Analysis

7 Conclusions and FutureWork

References

Glossary
Index

Автор: Ioannis Pitas
Название: Graph-Based Social Media Analysis
ISBN: 149871904X ISBN-13(EAN): 9781498719049
Издательство: Taylor&Francis
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Цена: 107190.00 T
Наличие на складе: Невозможна поставка.
Описание:

Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear algebra, digital media, machine learning, big data analysis, and signal processing.

Supplying an overview of graph-based social media analysis, the book provides readers with a clear understanding of social media structure. It uses graph theory, particularly the algebraic description and analysis of graphs, in social media studies.

The book emphasizes the big data aspects of social and digital media. It presents various approaches to storing vast amounts of data online and retrieving that data in real-time. It demystifies complex social media phenomena, such as information diffusion, marketing and recommendation systems in social media, and evolving systems. It also covers emerging trends, such as big data analysis and social media evolution.

Describing how to conduct proper analysis of the social and digital media markets, the book provides insights into processing, storing, and visualizing big social media data and social graphs. It includes coverage of graphs in social and digital media, graph and hyper-graph fundamentals, mathematical foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking, label propagation and diffusion in social media, graph-based pattern recognition and machine learning, graph-based pattern classification and dimensionality reduction, and much more.

This book is an ideal reference for scientists and engineers working in social media and digital media production and distribution. It is also suitable for use as a textbook in undergraduate or graduate courses on digital media, social media, or social networks.

Автор: Francesco Mola; Claudio Conversano; Maurizio Vichi
Название: Classification, (Big) Data Analysis and Statistical Learning
ISBN: 3319557076 ISBN-13(EAN): 9783319557076
Издательство: Springer
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Цена: 102480.00 T
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Описание: This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.

Автор: Christian Borgelt; Mar?a ?ngeles Gil; Jo?o M.C. So
Название: Towards Advanced Data Analysis by Combining Soft Computing and Statistics
ISBN: 3642443745 ISBN-13(EAN): 9783642443749
Издательство: Springer
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Цена: 139310.00 T
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Описание: This book blends the adaptability and speed of soft computing with the rigor and precision of statistics to enhance the robustness and generalizability of data analysis, while preserving the flexibility to solve real-world problems intuitively and efficiently.

Автор: Zhang Rong Et Al
Название: Review Comment Analysis For E-Commerce
ISBN: 9813100044 ISBN-13(EAN): 9789813100046
Издательство: World Scientific Publishing
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Цена: 79200.00 T
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Описание: This book presents the recent achievements on the processing of representative user generated content (UGC) on E-commerce websites. This large size of UGC is valuable information for data mining to help customer/object profiling. It provides a comprehensive overview on the concept of customer credibility, object-oriented review summarization technology and content-based collaborative filtering algorithm. It covers a feedback mechanism which is designed to discover customer credibility, which is used to define the professional degree of review content; product-oriented review summarization for restaurants or trip arrangements, and introduced content-based collaborative filtering for product recommendation.

Автор: Dariusz Kr?l; Lech Madeyski; Ngoc Thanh Nguyen
Название: Recent Developments in Intelligent Information and Database Systems
ISBN: 3319312766 ISBN-13(EAN): 9783319312767
Издательство: Springer
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Цена: 139310.00 T
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Описание: Part I: Computational Intelligence in Data Mining and Machine Learning.- Part II: Ontologies, Social Networks and Recommendation Systems.- Part III: Web Services, Cloud Computing, Security and IntelligentInternet Systems.- Part IV: Knowledge Management and Language Processing.- Part V: Image, Video, Motion Analysis and Recognition.- Part VI: Advanced Computing Applications and Technologies.

Автор: J.-L. Starck; F. Murtagh
Название: Astronomical Image and Data Analysis
ISBN: 3642433537 ISBN-13(EAN): 9783642433535
Издательство: Springer
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Цена: 130430.00 T
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Описание: to Applications and Methods.- Filtering.- Deconvolution.- Detection.- Image Compression.- Multichannel Data.- An Entropic Tour of Astronomical Data Analysis.- Astronomical Catalog Analysis.- Multiple Resolution in Data Storage and Retrieval.- Towards the Virtual Observatory.

Автор: Christian Moewes; Andreas N?rnberger
Название: Computational Intelligence in Intelligent Data Analysis
ISBN: 3642430856 ISBN-13(EAN): 9783642430855
Издательство: Springer
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Цена: 174130.00 T
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Описание: Complex systems and their phenomena are ubiquitous as they can befound in biology, finance, the humanities, management sciences,medicine, physics and similar fields.For many problems in these fields, there are no conventional ways tomathematically or analytically solve them completely at low cost.