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Author: Edoardo M. Airoldi
Publisher: CRC Press
ISBN: 1466504080
Category : Computers
Languages : en
Pages : 622
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Book Description
In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.
Author: Edoardo M. Airoldi
Publisher: CRC Press
ISBN: 1466504080
Category : Computers
Languages : en
Pages : 622
Get Book Here
Book Description
In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.
Author: Edoardo M. Airoldi
Publisher: CRC Press
ISBN: 1466504099
Category : Computers
Languages : en
Pages : 608
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Book Description
Incorporating more than 20 years of the editors' and contributors' statistical work in mixed membership modeling, this handbook shows how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, readers will discover how to characterize complex multivariate data in a range of areas.
Author: Alina A. von Davier
Publisher: Springer
ISBN: 3319332619
Category : Education
Languages : en
Pages : 343
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Book Description
This edited volume provides a platform for experts from various fields to introduce and discuss their different perspectives on the topic of teamwork and collaborative problem solving. It brings together researchers in organizational teaming, educational collaboration, tutoring, simulation, and gaming as well as those involved in statistical and psychometric process modelling. This book seeks to channel this expertise towards advances in the measurement and assessment of cognitive and non-cognitive skills of individuals and teams.
Author: Jeroen Huisman
Publisher: Emerald Group Publishing
ISBN: 1787692787
Category : Education
Languages : en
Pages : 260
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Book Description
This volume of Theory and Method in Higher Education Research contains analyses and discussions of, amongst others, topic modelling, geometric data analysis,creativity and playfulness, longitudinal network analysis, grounded theory methods and autonetnography.
Author: Alan Julian Izenman
Publisher: Cambridge University Press
ISBN: 1108835767
Category : Mathematics
Languages : en
Pages : 501
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Book Description
This is the first book to describe modern methods for analyzing complex networks arising from a wide range of disciplines.
Author: J Ramon Gil-Garcia
Publisher: Springer
ISBN: 3319617621
Category : Political Science
Languages : en
Pages : 434
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Book Description
This book provides a comprehensive approach to the study of policy analytics, modelling and informatics. It includes theories and concepts for understanding tools and techniques used by governments seeking to improve decision making through the use of technology, data, modelling, and other analytics, and provides relevant case studies and practical recommendations. Governments around the world face policy issues that require strategies and solutions using new technologies, new access to data and new analytical tools and techniques such as computer simulation, geographic information systems, and social network analysis for the successful implementation of public policy and government programs. Chapters include cases, concepts, methodologies, theories, experiences, and practical recommendations on data analytics and modelling for public policy and practice, and addresses a diversity of data tools, applied to different policy stages in several contexts, and levels and branches of government. This book will be of interest of researchers, students, and practitioners in e-government, public policy, public administration, policy analytics and policy informatics.
Author: Justin Grimmer
Publisher: Princeton University Press
ISBN: 0691207992
Category : Social Science
Languages : en
Pages : 360
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Book Description
A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry
Author: Ibrahim Arpaci
Publisher: Springer Nature
ISBN: 3030677168
Category : Technology & Engineering
Languages : en
Pages : 385
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Book Description
This book tackles the recent research directions in using the newly emerged technologies during the era of COVID-19 pandemic. It mainly focuses on using emerging technologies and their impact on health care, education, and society. It also provides insights into the current challenges and constraints in using technologies during the era of COVID-19 pandemic and exposes new opportunities for future research in the domain.
Author: D. Betsy McCoach
Publisher: SAGE
ISBN: 1529711088
Category : Social Science
Languages : en
Pages : 198
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Book Description
Using simple and direct language, this concise text provides practical guidance on a wide range of modeling methods and techniques for use with quantitative data. It covers: · 2-level Multilevel Models · Structural Equation Modeling (SEM) · Longitudinal Modeling using multilevel and SEM techniques · Combining organizational and longitudinal models Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
Author: Muhammed Fatih Kaya
Publisher: Springer Nature
ISBN: 3658405341
Category : Business & Economics
Languages : en
Pages : 178
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Book Description
The world of digitalisation is changing the way how people and business companies communicate with each other. Electronic negotiations represent one of the most important forms of business communication and can influence the successes and failures of companies in a significant way, whether in interorganisational or intraorganisational processes. Analysing negotiation interactions to determine pattern-based peculiarities in the communication offers new value-adding information concerning the management of optimised communication processes, even though the machine-based processing of communication data bears a series of challenges. The present book develops a new approach to analyse the automated pattern recognition potential of Machine Learning methods in unstructured negotiation communication. It presents holistic research frameworks for the effective detection of structural patterns and reveals the pattern labelling potential in high-dimensional communication data by analytically implementing a series of Machine Learning methods.
