Literatur zur Informationserschließung

Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.

© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 16. Dezember 2019)

Suchergebnisse

• 1
  Lu, J. ; Xu, Q.: Ontologies and big data considerations for effective intelligence.
  Hershey, PA : IGI Global, 2017. 632 S.
  ISBN 9781522520580
  (Advances in information quality and management (AIQM) book series)
  
  Abstract: Ontologies and Big Data Considerations for Effective Intelligence is a key source on the latest advancements in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. Featuring extensive coverage across a range of relevant perspectives and topics, such as visual analytics, spatial databases, retrieval systems, and ontology models, this book is ideally designed for researchers, graduate students, academics, and industry professionals seeking ways to optimize knowledge management processes.
  
  Inhalt: Inhalt: Interactive visual analytics of big data / Carson K.-S. Leung [and 4 others] --Knowledge discovery for large databases in education institutes / Robab Saadatdoost [and 3 others] --Spatial databases: an overview / Grace L. Samson [and 3 others] -- The impact of the mode of data representation for the result quality of the detection and filtering of spam / Reda Mohamed Hamou, Abdelmalek Amine, Moulay Tahar -- Debunking intermediary censorship framework in social media via a content retrieval and classification software / Baramee Navanopparatskul, Sukree Sinthupinyo, Pirongrong Ramasoota -- Semantic approach to web-based discovery of unknowns to enhance intelligence gathering / Natalia Danilova, David Stupples -- Securing financial XML transactions using intelligent fuzzy classification techniques: a smart fuzzy-based model for financial XML transactions security using XML encryption / Faisal Tawfiq Ammari, Joan Lu -- Building a secured XML real-time interactive data exchange architecture / Yousef E. Rabadi, Joan Lu -- User query enhancement for behavioral targeting / Wei Xiong, Y. F. Brook Wu -- A generic model of ontology to visualize information science domain (OIS) / Ahlam F. Sawsaa, Joan Lu -- Research background on ontology / Ahlam F. Sawsaa, Joan Lu -- Methodology of creating ontology of information science (OIS) / Ahlam F. Sawsaa, Joan Lu -- Modelling design of OIS ontology / Ahlam F. Sawsaa, Joan Lu Findings for ontology in IS and discussion / Ahlam F. Sawsaa, Joan Lu -- Final remarks for the investigation in ontology in IS and possible future directions / Ahlam F. Sawsaa, Joan Lu.
  
  Anmerkung: DOI: 10.4018/978-1-5225-2058-0.
  
  
  LCSH: Semantic Web. ; Ontologies (Information retrieval) ; Big data
  
• 2
  O'Neil, C.: Angriff der Algorithmen : wie sie Wahlen manipulieren, Berufschancen zerstören und unsere Gesundheit gefährden.Aus dem Englischen von Karsten Petersen.
  München : Hanser, 2017. 336 S.
  ISBN 978-3-446-25668-2
  
  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. ; A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life - and threaten to rip apart our social fabric. We live in the age of the algorithm. Increasingly, the decisions that affect our lives - where we go to school, whether we get a loan, how much we pay for insurance - are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: everyone is judged according to the same rules, and bias is eliminated. And yet, as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and incontestable, even when they're wrong. Most troubling, they reinforce discrimination. Tracing the arc of a person's life, O'Neil exposes the black box models that shape our future, both as individuals and as a society. These "weapons of math destruction" score teachers and students, sort CVs, grant or deny loans, evaluate workers, target voters, and monitor our health. O'Neil calls on modellers to take more responsibility for their algorithms and on policy makers to regulate their use. But in the end, it's up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.
  
  Inhalt: Kommentare: 'Fascinating and deeply disturbing' - Yuval Noah Harari, Guardian Books of the Year 'A manual for the 21st-century citizen... accessible, refreshingly critical, relevant and urgent' - Federica Cocco, Financial Times
  
  Anmerkung: 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/.
  
  Wissenschaftsfach: Informatik
  
  LCSH: Big data / Social aspects / United States ; Big data / Political aspects / United States ; Social indicators / Mathematical models / Moral and ethical aspects ; Democracy / United States ; United States / Social conditions / 21st century
  RSWK: Massendaten / Kritik / Soziale Ungleichheit
  BK: 71.52 Kulturelle Prozesse Soziologie ; 54.08 (Informatik in Beziehung zu Mensch und Gesellschaft) ; 71.43 (Technologische Faktoren)
  ASB: Gcm
  DDC: 005.7 / dc23
  SFB: Soz 943
  GHBS: OGH (PB)
  KAB: E 711
  LCC: QA76.9.B45
  SSD: GCV
  RVK: SR 850 ; ST 530 ; MS 7965