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  • × classification_ss:"ST 530"
  • × type_ss:"m"
  • × year_i:[2010 TO 2020}
  1. Geiselberger, H. u.a. [Red.]: Big Data : das neue Versprechen der Allwissenheit (2013) 0.00 
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    Abstract
    Der Begriff Big Data hat spätestens in diesem Jahr der Überwachung den Durchbruch geschafft - mit dem Sammelband des Suhrkamp Verlags bekommt nun jedermann den Data-Durchblick. ... Experten aus Theorie und Praxis bringen ihre Erfahrungen und Meinungen im Suhrkamp-Werk kurz und präzise auf den Punkt und bieten damit einen guten Überblick über die Thematik, die gerade erst in den Startlöchern steht.
    BK
    54.08 Informatik in Beziehung zu Mensch und Gesellschaft
    Classification
    54.08 Informatik in Beziehung zu Mensch und Gesellschaft
  2. O'Neil, C.: Angriff der Algorithmen : wie sie Wahlen manipulieren, Berufschancen zerstören und unsere Gesundheit gefährden (2017) 0.00 
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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.
    BK
    54.08 (Informatik in Beziehung zu Mensch und Gesellschaft)
    Classification
    54.08 (Informatik in Beziehung zu Mensch und Gesellschaft)
    Footnote
    Originaltitel: Weapons of math destruction:: how Big Data increases inequality and threatens democracy. Vgl. auch den Rezensions-Beitrag: Krüger, J.: Wie der Mensch die Kontrolle über den Algorithmus behalten kann. [19.01.2018]. In: https://netzpolitik.org/2018/algorithmen-regulierung-im-kontext-aktueller-gesetzgebung/.
  3. Mining text data (2012) 0.00 
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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.
    Isbn
    978-1-4614-3222-7
  4. Liu, B.: Web data mining : exploring hyperlinks, contents, and usage data (2011) 0.00 
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    Content
    Inhalt: 1. Introduction 2. Association Rules and Sequential Patterns 3. Supervised Learning 4. Unsupervised Learning 5. Partially Supervised Learning 6. Information Retrieval and Web Search 7. Social Network Analysis 8. Web Crawling 9. Structured Data Extraction: Wrapper Generation 10. Information Integration

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