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Abstract

Algorithmen nehmen Einfluss auf unser Leben: Von ihnen hängt es ab, ob man etwa einen Kredit für sein Haus erhält und wie viel man für die Krankenversicherung bezahlt. Cathy O'Neil, ehemalige Hedgefonds-Managerin und heute Big-Data-Whistleblowerin, erklärt, wie Algorithmen in der Theorie objektive Entscheidungen ermöglichen, im wirklichen Leben aber mächtigen Interessen folgen. Algorithmen nehmen Einfluss auf die Politik, gefährden freie Wahlen und manipulieren über soziale Netzwerke sogar die Demokratie. Cathy O'Neils dringlicher Appell zeigt, wie sie Diskriminierung und Ungleichheit verstärken und so zu Waffen werden, die das Fundament unserer Gesellschaft erschüttern.

RSWK

Massendaten / Kritik / Soziale Ungleichheit

Subject

Massendaten / Kritik / Soziale Ungleichheit

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Abstract

This book offers a comprehensive introduction to the exploding field of data mining. We are surrounded by data, numerical and otherwise, which must be analyzed and processed to convert it into information that informs, instructs, answers, or otherwise aids understanding and decision-making. Due to the ever-increasing complexity and size of today's data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis. "Data Mining: Concepts, Models, Methods, and Algorithms" discusses data mining principles and then describes representative state-of-the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples. This text offers guidance: how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided. This book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. Data mining is an exploding field and this book offers much-needed guidance to selecting among the numerous analysis programs that are available.

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Abstract

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

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Theme

Bibliographische Software