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: Centrality and Diversity in Search
    sub title: Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition
  name:
    name part: Murty, M.N.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Biswas, Anirban.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 94 p. 17 illus., 5 illus. in color. online resource.
  abstract: The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification. The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition. .
  table of contents: Introduction -- Searching -- Representation -- Clustering and Classification -- Ranking -- Centrality and Diversity in Social and Information Networks -- Conclusion.
  note: by M.N. Murty, Anirban Biswas.
  subject:
    topic: Machine learning
  subject:
    topic: Pattern recognition
  subject:
    topic: Machine Learning
  subject:
    topic: Pattern Recognition
  classification: Q325.5-.7
  classification: TK7882.P3
  classification: 006.31
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics
  identifier: 9783030247133
  identifier: https://doi.org/10.1007/978-3-030-24713-3
  record info:
    record creation date: 190814
    record change date: 20191026002417.0
    record identifier: 978-3-030-24713-3