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Text Mining
The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te
Explaining the History of American Foreign Relations
This volume presents substantially revised and new essays on methodology and approaches in foreign and international relations history.
Web and Big Data
This two-volume set, LNCS 10987 and 10988, constitutes the thoroughly refereed proceedings of the Second International Joint Conference, APWeb-WAIM 2018, held in Macau, China in July 2018. The 40 full papers presented together with 30 short papers, 6 demonstration papers and 3 keynotes were carefully reviewed and selected from 168 submissions. The papers are organized around the following topics: Text Analysis, Social Networks, Recommender Systems, Information Retrieval, Machine Learning, Knowledge Graphs, Database and Web Applications, Data Streams, Data Mining and Application, Query Processing, Big Data and Blockchain.
The Dangerous Art of Text Mining
The Dangerous Art of Text Mining celebrates the bold new research now possible because of text mining: the art of counting words over time. However, this book also presents a warning: without help from the humanities, data science can distort the past and lead to perilous errors. The book opens with a rogue's gallery of errors, then tours the ground-breaking analyses that have resulted from collaborations between humanists and data scientists. Jo Guldi explores how text mining can give a glimpse of the changing history of the past - for example, how quickly Americans forgot the history of slavery. Textual data can even prove who was responsible in Congress for silencing environmentalism over recent decades. The book ends with an impassioned vision of what text mining in defence of democracy would look like, and why humanists need to be involved.
Advances in Neural Information Processing Systems 16
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.
Computational Social Science
Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy.
Veridical Data Science
Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science. Most textbooks present data science as a linear analytic process involving a set of statistical and computational techniques without accounting for the challenges intrinsic to real-world applications. Veridical Data Science, by contrast, embraces the reality that most projects begin with an ambiguous domain question and messy data; it acknowledges that datasets are mere approximations of reality while analyses are mental constructs. Bin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to...
Towards the Future Internet
Emerging Trends from European Research. BThe way the book is structured and enhanced makes it an ideal reference book for managers, academics, researchers and system designers in the communications field./B BRBRI- Harry Skianis, Computing Reviews about the 2009 edition of Towards
Handbook of Mixed Membership Models and Their Applications
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.
Discourse Processing
Discourse Processing here is framed as marking up a text with structural descriptions on several levels, which can serve to support many language-processing or text-mining tasks. We first explore some ways of assigning structure on the document level: the logical document structure as determined by the layout of the text, its genre-specific content structure, and its breakdown into topical segments. Then the focus moves to phenomena of local coherence. We introduce the problem of coreference and look at methods for building chains of coreferring entities in the text. Next, the notion of coherence relation is introduced as the second important factor of local coherence. We study the role of c...
