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: Reasoning Web. Explainable Artificial Intelligence
    sub title: 15th International Summer School 2019, Bolzano, Italy, September 20-24, 2019, Tutorial Lectures
  name:
    name part: Krötzsch, Markus.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Stepanova, Daria.
    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: 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, 283 p. 366 illus., 23 illus. in color. online resource.
  abstract: The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.
  table of contents: Classical Algorithms for Reasoning and Explanation in Description Logics -- Explanation-Friendly Query Answering Under Uncertainty -- Provenance in Databases: Principles and Applications -- Knowledge Representation and Rule Mining in Entity-Centric Knowledge Bases -- Explaining Data with Formal Concept Analysis -- Logic-based Learning of Answer Set Programs -- Constraint Learning: An Appetizer -- A Modest Markov Automata Tutorial -- Explainable AI Planning (XAIP): Overview and the Case of Contrastive.
  note: edited by Markus Krötzsch, Daria Stepanova.
  subject:
    topic: Database management
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
  subject:
    topic: Application software
  subject:
    topic: Mathematical logic
  subject:
    topic: Database Management
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Computer Appl. in Administrative Data Processing
  subject:
    topic: Mathematical Logic and Formal Languages
  classification: QA76.9.D3
  classification: 005.74
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Information Systems and Applications, incl. Internet/Web, and HCI ; 11810
  identifier: 9783030314231
  identifier: https://doi.org/10.1007/978-3-030-31423-1
  record info:
    record creation date: 190917
    record change date: 20191028081828.0
    record identifier: 978-3-030-31423-1