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Analysis of Large and Complex Data
  • Language: en
  • Pages: 640

Analysis of Large and Complex Data

  • Type: Book
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  • Published: 2016-08-03
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  • Publisher: Springer

This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.

Recent Trends and Future Challenges in Learning from Data
  • Language: en
  • Pages: 158

Recent Trends and Future Challenges in Learning from Data

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Data Analysis and Classification
  • Language: en
  • Pages: 473

Data Analysis and Classification

The volume provides results from the latest methodological developments in data analysis and classification and highlights new emerging subjects within the field. It contains articles about statistical models, classification, cluster analysis, multidimensional scaling, multivariate analysis, latent variables, knowledge extraction from temporal data, financial and economic applications, and missing values. Papers cover both theoretical and empirical aspects.

Computational Conflict Research
  • Language: en
  • Pages: 270

Computational Conflict Research

This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated co...

COMPSTAT
  • Language: en
  • Pages: 508

COMPSTAT

This Volume contains the Keynote, Invited and Full Contributed papers presented at COMPSTAT'98. A companion volume (Payne & Lane, 1998) contains papers describing the Short Communications and Posters. COMPSTAT is a one-week conference held every two years under the auspices of the International Association of Statistical Computing, a section of the International Statistical Institute. COMPSTAT'98 is organised by IACR-Rothamsted, IACR-Long Ashton, the University of Bristol Department of Mathematics and the University of Bath Department of Mathematical Sciences. It is taking place from 24-28 August 1998 at University of Bristol. Previous COMPSTATs (from 1974-1996) were in Vienna, Berlin, Leide...

Handbook on Peacekeeping and International Relations
  • Language: en
  • Pages: 409

Handbook on Peacekeeping and International Relations

Integrating comparative empirical studies with cutting-edge theory, this dynamic Handbook provides a comprehensive overview of the study and practice of peacekeeping. Han Dorussen brings together a diverse range of contributions which represent the most recent generation of peacekeeping research, embodying notable shifts in the kinds of questions asked as well as the data and methods employed.

Classification, (Big) Data Analysis and Statistical Learning
  • Language: en
  • Pages: 243

Classification, (Big) Data Analysis and Statistical Learning

  • Type: Book
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  • Published: 2018-02-21
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  • Publisher: Springer

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.

Diversification, Relatedness, and Performance
  • Language: en
  • Pages: 229

Diversification, Relatedness, and Performance

Frithjof Pils uses multiple statistical techniques to examine the true nature of the relationships between diversification strategies and accounting-based, market-based, and growth-based performance. The author shows implications for the interpretation of past research, the design of future research including the use of meta-analysis methodologies, as well as management practice.

Classification and Data Science in the Digital Age
  • Language: en
  • Pages: 393

Classification and Data Science in the Digital Age

The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and modeling to clustering and dimension reduction, from functional data analysis to time series analysis, and network analysis. The applications reflect new analyses in a variety of fields, including medicine, marketing, genetics, engineering, and education. The book comprises selected and peer-reviewed papers presented at the 17th Conference of the International Federation of Classification Societies (IFCS 2022), held in Porto, Portugal, July 19–23, 2022. Th...

What Do We Know about Civil Wars?
  • Language: en
  • Pages: 423

What Do We Know about Civil Wars?

Civil wars remain the most frequent and deadly form of organized armed conflict in the world. What Do We Know about Civil Wars? enlists leading scholars to guide students through cutting-edge research on civil war onset, duration, and outcomes, as well as the recurrence and consequences of civil wars to better understand global security.