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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
A Book

by Gary Miner

  • Publisher : Academic Press
  • Release : 2012
  • Pages : 1053
  • ISBN : 012386979X
  • Language : En, Es, Fr & De
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The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. -Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible -Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com -Glossary of text mining terms provided in the appendix

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2012
  • Pages : 1053
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities"

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
A Book

by Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen

  • Publisher : Academic Press
  • Release : 2012-01-25
  • Pages : 1000
  • ISBN : 0123870119
  • Language : En, Es, Fr & De
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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. Winner of a 2012 PROSE Award in Computing and Information Sciences from the Association of American Publishers, this book presents a comprehensive how-to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com Glossary of text mining terms provided in the appendix

Practical Text Analytics

Practical Text Analytics
Maximizing the Value of Text Data

by Murugan Anandarajan,Chelsey Hill,Thomas Nolan

  • Publisher : Springer
  • Release : 2018-10-19
  • Pages : 285
  • ISBN : 3319956639
  • Language : En, Es, Fr & De
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This book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media. Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information.

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
A Book

by Robert Nisbet,Gary Miner,Ken Yale

  • Publisher : Elsevier
  • Release : 2017-11-09
  • Pages : 822
  • ISBN : 0124166458
  • Language : En, Es, Fr & De
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Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Practical Predictive Analytics and Decisioning Systems for Medicine

Practical Predictive Analytics and Decisioning Systems for Medicine
Informatics Accuracy and Cost-Effectiveness for Healthcare Administration and Delivery Including Medical Research

by Linda Miner,Pat Bolding,Joseph Hilbe,Mitchell Goldstein,Thomas Hill,Robert Nisbet,Nephi Walton,Gary Miner

  • Publisher : Academic Press
  • Release : 2014-09-27
  • Pages : 1110
  • ISBN : 012411640X
  • Language : En, Es, Fr & De
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With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner. Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions. Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations Demonstrates methods to help sort through data to make better observations and allow you to make better predictions

Practical Text Analytics

Practical Text Analytics
Interpreting Text and Unstructured Data for Business Intelligence

by Steven Struhl

  • Publisher : Kogan Page Publishers
  • Release : 2015-07-03
  • Pages : 272
  • ISBN : 0749474025
  • Language : En, Es, Fr & De
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In an age where customer opinion and feedback can have an immediate, major effect upon the success of a business or organization, marketers must have the ability to analyze unstructured data in everything from social media and internet reviews to customer surveys and phone logs. Practical Text Analytics is an essential daily reference resource, providing real-world guidance on the effective application of text analytics. The book presents the analysis process so that it is immediately understood by the marketing professionals who must use it, so they can apply proven concepts and methods correctly and with confidence. By decoding industry terminology and demonstrating practical application of data models once reserved for experts, Practical Text Analytics shows marketers how to frame the right questions, identify key themes and find hidden meaning from unstructured data. Readers will learn to develop powerful new marketing strategies to elevate customer experience, solidify brand value and elevate reputation. Online resources include self-test questions, chapter review Q&A and an Instructor's Manual with text sources and instructions.

Text Mining and Visualization

Text Mining and Visualization
Case Studies Using Open-Source Tools

by Markus Hofmann,Andrew Chisholm

  • Publisher : CRC Press
  • Release : 2016-01-05
  • Pages : 337
  • ISBN : 148223758X
  • Language : En, Es, Fr & De
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Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributors-all highly experienced with text mining and open-source software-explain how text data are gathered and processed from a w

11th International Conference on Practical Applications of Computational Biology & Bioinformatics

11th International Conference on Practical Applications of Computational Biology & Bioinformatics
A Book

by Florentino Fdez-Riverola,Mohd Saberi Mohamad,Miguel Rocha,Juan F. De Paz,Tiago Pinto

  • Publisher : Springer
  • Release : 2017-06-19
  • Pages : 330
  • ISBN : 3319608169
  • Language : En, Es, Fr & De
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Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance in boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. The PACBB’17 conference was intended to contribute to this effort and promote this fruitful interaction, with a technical program that included 39 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Further, the conference promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists).

Recent Studies on Risk Analysis and Statistical Modeling

Recent Studies on Risk Analysis and Statistical Modeling
A Book

by Teresa A. Oliveira,Christos P. Kitsos,Amílcar Oliveira,Luís Grilo

  • Publisher : Springer
  • Release : 2018-08-22
  • Pages : 375
  • ISBN : 3319766058
  • Language : En, Es, Fr & De
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This book provides an overview of the latest developments in the field of risk analysis (RA). Statistical methodologies have long-since been employed as crucial decision support tools in RA. Thus, in the context of this new century, characterized by a variety of daily risks - from security to health risks - the importance of exploring theoretical and applied issues connecting RA and statistical modeling (SM) is self-evident. In addition to discussing the latest methodological advances in these areas, the book explores applications in a broad range of settings, such as medicine, biology, insurance, pharmacology and agriculture, while also fostering applications in newly emerging areas. This book is intended for graduate students as well as quantitative researchers in the area of RA.

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
A Book

by Robert Nisbet,John Fletcher Elder,Gary Miner

  • Publisher : Academic Press
  • Release : 2009
  • Pages : 824
  • ISBN : 9780123747655
  • Language : En, Es, Fr & De
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This comprehensive professional reference for scientists, engineers, and researchers brings together in a single resource all the information a beginner will need to rapidly learn how to conduct data mining and the statistical analysis required to interpret the data once mined. A glossary of data mining terms provided in the appendix.

Practical Chemoinformatics

Practical Chemoinformatics
A Book

by Muthukumarasamy Karthikeyan,Renu Vyas

  • Publisher : Springer
  • Release : 2014-05-06
  • Pages : 533
  • ISBN : 8132217802
  • Language : En, Es, Fr & De
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Chemoinformatics is equipped to impact our life in a big way mainly in the fields of chemical, medical and material sciences. This book is a product of several years of experience and passion for the subject written in a simple lucid style to attract the interest of the student community who wish to master chemoinformatics as a career. The topics chosen cover the entire spectrum of chemoinformatics activities (methods, data and tools). The algorithms, open source databases, tutorials supporting theory using standard datasets, guidelines, questions and do it yourself exercises will make it valuable to the academic research community. At the same time every chapter devotes a section on development of new software tools relevant for the growing pharmaceutical, fine chemicals and life sciences industry. The book is intended to assist beginners to hone their skills and also constitute an interesting reading for the experts.

8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014)

8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014)
A Book

by Julio Saez-Rodriguez,Miguel P. Rocha,Florentino Fdez-Riverola,Juan F. De Paz Santana

  • Publisher : Springer
  • Release : 2014-05-21
  • Pages : 294
  • ISBN : 3319075810
  • Language : En, Es, Fr & De
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Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘14 contributes to this effort promoting this fruitful interaction. PACBB'14 technical program included 34 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference promotes the interaction of scientists from diverse research groups and with a distinct background such as computer scientists, mathematicians or biologists.

Data Mining in Dynamic Social Networks and Fuzzy Systems

Data Mining in Dynamic Social Networks and Fuzzy Systems
A Book

by Bhatnagar, Vishal

  • Publisher : IGI Global
  • Release : 2013-06-30
  • Pages : 412
  • ISBN : 1466642149
  • Language : En, Es, Fr & De
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Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data. Data Mining in Dynamic Social Networks and Fuzzy Systems brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organizational development.

Computational Intelligence Applications in Business Intelligence and Big Data Analytics

Computational Intelligence Applications in Business Intelligence and Big Data Analytics
A Book

by Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu

  • Publisher : CRC Press
  • Release : 2017-06-26
  • Pages : 362
  • ISBN : 1351720244
  • Language : En, Es, Fr & De
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There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

Capturing, Analyzing, and Managing Word-of-Mouth in the Digital Marketplace

Capturing, Analyzing, and Managing Word-of-Mouth in the Digital Marketplace
A Book

by Rathore, Sumangla

  • Publisher : IGI Global
  • Release : 2015-08-28
  • Pages : 309
  • ISBN : 1466694505
  • Language : En, Es, Fr & De
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With the growth of information technology—and the Internet in particular—many new communication channels and platforms have emerged. These platforms are focused on being not only user friendly, but also highly interactive, providing many unique ways to create and distribute content. Capturing, Analyzing, and Managing Word-of-Mouth in the Digital Marketplace explores the way these new channels and platforms affect our everyday interactions, particularly as they relate to meaning, growth, and recent trends, practices, issues, and challenges surrounding the world of modern marketing. Featuring a special emphasis on social media, blogging, viral marketing, and other forms of e-communication, this timely reference source is essential for students, researchers, academics, and marketing practitioners.

Data Mining Applications with R

Data Mining Applications with R
A Book

by Yanchang Zhao,Yonghua Cen

  • Publisher : Academic Press
  • Release : 2013-11-26
  • Pages : 514
  • ISBN : 0124115209
  • Language : En, Es, Fr & De
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Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries Presents various case studies in real-world applications, which will help readers to apply the techniques in their work Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques
A Guide to Data Science for Fraud Detection

by Bart Baesens,Veronique Van Vlasselaer,Wouter Verbeke

  • Publisher : John Wiley & Sons
  • Release : 2015-07-27
  • Pages : 400
  • ISBN : 1119146836
  • Language : En, Es, Fr & De
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Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.

Big Data Management, Technologies, and Applications

Big Data Management, Technologies, and Applications
A Book

by Hu, Wen-Chen

  • Publisher : IGI Global
  • Release : 2013-10-31
  • Pages : 342
  • ISBN : 1466647000
  • Language : En, Es, Fr & De
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"This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--Provided by publisher.

Recent Advances in Information Systems and Technologies

Recent Advances in Information Systems and Technologies
Volume 1

by Álvaro Rocha,Ana Maria Correia,Hojjat Adeli,Luís Paulo Reis,Sandra Costanzo

  • Publisher : Springer
  • Release : 2017-03-27
  • Pages : 930
  • ISBN : 3319565354
  • Language : En, Es, Fr & De
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This book presents a selection of papers from the 2017 World Conference on Information Systems and Technologies (WorldCIST'17), held between the 11st and 13th of April 2017 at Porto Santo Island, Madeira, Portugal. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges involved in modern Information Systems and Technologies research, together with technological developments and applications. The main topics covered are: Information and Knowledge Management; Organizational Models and Information Systems; Software and Systems Modeling; Software Systems, Architectures, Applications and Tools; Multimedia Systems and Applications; Computer Networks, Mobility and Pervasive Systems; Intelligent and Decision Support Systems; Big Data Analytics and Applications; Human–Computer Interaction; Ethics, Computers & Security; Health Informatics; Information Technologies in Education; and Information Technologies in Radiocommunications.