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Data Simplification

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Data Simplification

Data Simplification Book
Author : Jules J. Berman
Publisher : Morgan Kaufmann
Release : 2016-03-10
ISBN : 0128038543
Language : En, Es, Fr & De

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Book Description :

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data. Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user. Discusses data simplification principles, methods, and tools that must be studied and mastered Provides open source tools, free utilities, and snippets of code that can be reused and repurposed to simplify data Explains how to best utilize indexes to search, retrieve, and analyze textual data Shows the data scientist how to apply ontologies, classifications, classes, properties, and instances to data using tried and true methods

Data Preprocessing in Data Mining

Data Preprocessing in Data Mining Book
Author : Salvador García,Julián Luengo,Francisco Herrera
Publisher : Springer
Release : 2014-08-30
ISBN : 3319102478
Language : En, Es, Fr & De

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Book Description :

Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.

Topological Data Analysis for Scientific Visualization

Topological Data Analysis for Scientific Visualization Book
Author : Julien Tierny
Publisher : Springer
Release : 2018-01-16
ISBN : 3319715070
Language : En, Es, Fr & De

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Book Description :

Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases. With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.

Data Abstraction and Pattern Identification in Time series Data

Data Abstraction and  Pattern Identification  in Time series Data Book
Author : Prithiviraj Muthumanickam
Publisher : Linköping University Electronic Press
Release : 2019-11-25
ISBN : 9179299652
Language : En, Es, Fr & De

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Book Description :

Data sources such as simulations, sensor networks across many application domains generate large volumes of time-series data which exhibit characteristics that evolve over time. Visual data analysis methods can help us in exploring and understanding the underlying patterns present in time-series data but, due to their ever-increasing size, the visual data analysis process can become complex. Large data sets can be handled using data abstraction techniques by transforming the raw data into a simpler format while, at the same time, preserving significant features that are important for the user. When dealing with time-series data, abstraction techniques should also take into account the underlying temporal characteristics. This thesis focuses on different data abstraction and pattern identification methods particularly in the cases of large 1D time-series and 2D spatio-temporal time-series data which exhibit spatiotemporal discontinuity. Based on the dimensionality and characteristics of the data, this thesis proposes a variety of efficient data-adaptive and user-controlled data abstraction methods that transform the raw data into a symbol sequence. The transformation of raw time-series into a symbol sequence can act as input to different sequence analysis methods from data mining and machine learning communities to identify interesting patterns of user behavior. In the case of very long duration 1D time-series, locally adaptive and user-controlled data approximation methods were presented to simplify the data, while at the same time retaining the perceptually important features. The simplified data were converted into a symbol sequence and a sketch-based pattern identification was then used to identify patterns in the symbolic data using regular expression based pattern matching. The method was applied to financial time-series and patterns such as head-and-shoulders, double and triple-top patterns were identified using hand drawn sketches in an interactive manner. Through data smoothing, the data approximation step also enables visualization of inherent patterns in the time-series representation while at the same time retaining perceptually important points. Very long duration 2D spatio-temporal eye tracking data sets that exhibit spatio-temporal discontinuity was transformed into symbolic data using scalable clustering and hierarchical cluster merging processes, each of which can be parallelized. The raw data is transformed into a symbol sequence with each symbol representing a region of interest in the eye gaze data. The identified regions of interest can also be displayed in a Space-Time Cube (STC) that captures both the temporal and contextual information. Through interactive filtering, zooming and geometric transformation, the STC representation along with linked views enables interactive data exploration. Using different sequence analysis methods, the symbol sequences are analyzed further to identify temporal patterns in the data set. Data collected from air traffic control officers from the domain of Air traffic control were used as application examples to demonstrate the results.

Automatic Text Simplification

Automatic Text Simplification Book
Author : Horacio Saggion
Publisher : Springer Nature
Release : 2022-05-31
ISBN : 3031021665
Language : En, Es, Fr & De

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Book Description :

Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written—its vocabulary, its syntax—can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be difficult to read and understand by people as well as difficult to analyze by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience. The process usually involves the replacement of difficult or unknown phrases with simpler equivalents and the transformation of long and syntactically complex sentences into shorter and less complex ones. Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research not only because of the interesting challenges it posesses but also because of its social implications. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification. It also provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development together with text simplification evaluation techniques.

Digital Imaging for Cultural Heritage Preservation

Digital Imaging for Cultural Heritage Preservation Book
Author : Filippo Stanco,Sebastiano Battiato,Giovanni Gallo
Publisher : CRC Press
Release : 2011-07-28
ISBN : 1439821739
Language : En, Es, Fr & De

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Book Description :

This edition presents the most prominent topics and applications of digital image processing, analysis, and computer graphics in the field of cultural heritage preservation. The text assumes prior knowledge of digital image processing and computer graphics fundamentals. Each chapter contains a table of contents, illustrations, and figures that elucidate the presented concepts in detail, as well as a chapter summary and a bibliography for further reading. Well-known experts cover a wide range of topics and related applications, including spectral imaging, automated restoration, computational reconstruction, digital reproduction, and 3D models.

Impact Evaluation of Business License Simplification in Peru

Impact Evaluation of Business License Simplification in Peru Book
Author : World Bank
Publisher : World Bank Publications
Release : 2012-12-01
ISBN : 0821398024
Language : En, Es, Fr & De

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Book Description :

This report assessed the effects of reforms supported by the International Finance Corporation s Business License Simplification Project in Lima, Peru, and identified the main benefits as time and cost savings for businesses.

Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges

Machine Learning and Big Data Analytics Paradigms  Analysis  Applications and Challenges Book
Author : Aboul Ella Hassanien,Ashraf Darwish
Publisher : Springer Nature
Release : 2020-12-14
ISBN : 303059338X
Language : En, Es, Fr & De

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Book Description :

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

The Design of Management Information Systems for Mental Health Organizations

The Design of Management Information Systems for Mental Health Organizations Book
Author : Robert L. Chapman
Publisher : Unknown
Release : 1980
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download The Design of Management Information Systems for Mental Health Organizations book written by Robert L. Chapman, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Analysis of Neural Data

Analysis of Neural Data Book
Author : Robert E. Kass,Uri T. Eden,Emery N. Brown
Publisher : Springer
Release : 2014-07-08
ISBN : 1461496020
Language : En, Es, Fr & De

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Book Description :

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Analytics and Big Data for Accountants

Analytics and Big Data for Accountants Book
Author : Jim Lindell
Publisher : John Wiley & Sons
Release : 2018-03-23
ISBN : 1119512360
Language : En, Es, Fr & De

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Book Description :

Analytics is the new force driving business. Tools have been created to measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators, many using the unprecedented amount of data now flowing into organizations. Featuring updated examples and surveys, this dynamic book covers leading-edge topics in analytics and finance. It is packed with useful tips and practical guidance you can apply immediately. This book prepares accountants to: Deal with major trends in predictive analytics, optimization, correlation of metrics, and big data. Interpret and manage new trends in analytics techniques affecting your organization. Use new tools for data analytics. Critically interpret analytics reports and advise decision makers.

Benefits simplification

Benefits simplification Book
Author : Great Britain: Parliament: House of Commons: Work and Pensions Committee
Publisher : The Stationery Office
Release : 2007-07-26
ISBN : 9780215035509
Language : En, Es, Fr & De

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Book Description :

Benefits Simplification : Seventh report of session 2006-07, Vol. 2: Oral and written Evidence

BOOK ALONE Evidence Based Practice for Nurses

BOOK ALONE   Evidence Based Practice for Nurses Book
Author : Nola Schmidt,Janet Brown
Publisher : Jones & Bartlett Publishers
Release : 2011-02-05
ISBN : 0763794678
Language : En, Es, Fr & De

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Book Description :

Doody's Review Service - 5 Stars!The Second Edition of Evidence-Based Practice for Nurses: Appraisal and Application of Research continues to serve as the definitive reference for transitioning research into nursing practice. Based on the innovation-decision process (IDP), each unit is shaped according to the five steps of the IDP: knowledge, persuasion, decision, implementation, and confirmation. This unique organizational approach combined with updated case studies and ethical principles allows the research process to be tangible and linked with strategies that promote advancement.

Advanced Data Mining and Applications

Advanced Data Mining and Applications Book
Author : Xue Li,Shuliang Wang
Publisher : Springer Science & Business Media
Release : 2005-07-12
ISBN : 354027894X
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the First International Conference on Advanced Data Mining and Applications, ADMA 2005, held in Wuhan, China in July 2005. The conference was focused on sophisticated techniques and tools that can handle new fields of data mining, e.g. spatial data mining, biomedical data mining, and mining on high-speed and time-variant data streams; an expansion of data mining to new applications is also strived for. The 25 revised full papers and 75 revised short papers presented were carefully peer-reviewed and selected from over 600 submissions. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, text mining, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, security and privacy issues, spatial data mining, and streaming data mining.

Statistical Data Cleaning with Applications in R

Statistical Data Cleaning with Applications in R Book
Author : Mark van der Loo,Edwin de Jonge
Publisher : John Wiley & Sons
Release : 2018-01-29
ISBN : 1118897145
Language : En, Es, Fr & De

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Book Description :

A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses on the automation of data cleaning methods, including both theory and applications written in R. Enables the reader to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis. Explores statistical techniques for solving issues such as incompleteness, contradictions and outliers, integration of data cleaning components and quality monitoring. Supported by an accompanying website featuring data and R code. This book enables data scientists and statistical analysts working with data to deepen their understanding of data cleaning as well as to upgrade their practical data cleaning skills. It can also be used as material for a course in data cleaning and analyses.

Real Time Massive Model Rendering

Real Time Massive Model Rendering Book
Author : Sung-eui Yoon,Enrico Gobbetti,David Kasik,Dinesh Manocha
Publisher : Morgan & Claypool Publishers
Release : 2008-08-08
ISBN : 1598297937
Language : En, Es, Fr & De

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Book Description :

Interactive display and visualization of large geometric and textured models is becoming a fundamental capability. There are numerous application areas, including games, movies, CAD, virtual prototyping, and scientific visualization. One of observations about geometric models used in interactive applications is that their model complexity continues to increase because of fundamental advances in 3D modeling, simulation, and data capture technologies. As computing power increases, users take advantage of the algorithmic advances and generate even more complex models and data sets. Therefore, there are many cases where we are required to visualize massive models that consist of hundreds of millions of triangles and, even, billions of triangles. However, interactive visualization and handling of such massive models still remains a challenge in computer graphics and visualization. In this monograph we discuss various techniques that enable interactive visualization of massive models. These techniques include visibility computation, simplification, levels-of-detail, and cache-coherent data management.We believe that the combinations of these techniques can make it possible to interactively visualize massive models in commodity hardware. Table of Contents: Introduction / Visibility / Simplification and Levels of Detail / Alternative Representations / Cache-Coherent Data Management / Conclusions / Bibliography

Advanced Data Mining and Applications

Advanced Data Mining and Applications Book
Author : Xudong Luo,Jeffrey Xu Yu,Zhi Li
Publisher : Springer
Release : 2014-12-17
ISBN : 331914717X
Language : En, Es, Fr & De

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Book Description :

This book constitutes the proceedings of the 10th International Conference on Advanced Data Mining and Applications, ADMA 2014, held in Guilin, China during December 2014. The 48 regular papers and 10 workshop papers presented in this volume were carefully reviewed and selected from 90 submissions. They deal with the following topics: data mining, social network and social media, recommend systems, database, dimensionality reduction, advance machine learning techniques, classification, big data and applications, clustering methods, machine learning, and data mining and database.

Proceedings of the Fifteenth International Conference on Very Large Data Bases

Proceedings of the Fifteenth International Conference on Very Large Data Bases Book
Author : Petrus Maria Gerardus Apers,Gio Wiederhold
Publisher : Morgan Kaufmann
Release : 1989
ISBN : 9781558601017
Language : En, Es, Fr & De

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Book Description :

Download Proceedings of the Fifteenth International Conference on Very Large Data Bases book written by Petrus Maria Gerardus Apers,Gio Wiederhold, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.