rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Social Network Based Big Data Analysis and Applications
  name:
    name part: Kaya, Mehmet.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Kawash, Jalal.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Khoury, Suheil.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Day, Min-Yuh.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 249 p. 89 illus., 77 illus. in color. online resource.
  abstract: This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
  table of contents: Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.
  note: edited by Mehmet Kaya, Jalal Kawash, Suheil Khoury, Min-Yuh Day.
  subject:
    topic: Social sciences-Data processing
  subject:
    topic: Social sciences-Computer programs
  subject:
    topic: Big data
  subject:
    topic: Data mining
  subject:
    topic: Physics
  subject:
    topic: Computational Social Sciences
  subject:
    topic: Big Data
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Applications of Graph Theory and Complex Networks
  classification: H61.3
  classification: 300.00285
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Social Networks
  identifier: 9783319781969
  identifier: https://doi.org/10.1007/978-3-319-78196-9
  record info:
    record creation date: 180510
    record change date: 20191025052421.0
    record identifier: 978-3-319-78196-9