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: Building knowledge graphs
    sub title: a practitioner's guide
  name:
    name part: Barrasa, Jesús
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Webber, James.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: cau
    place:
      place term: Sebastopol
    publisher: O'Reilly Media, Incorporated
    date issued: 2023
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by storing interlinked descriptions of entities--objects, events, situations, or abstract concepts--and encoding the underlying information. How do you create a knowledge graph? And how do you move it from theory into production? Using hands-on examples, this practical book shows data scientists and data engineers how to build their own knowledge graphs. Authors Jesús Barrasa and Jim Webber from Neo4j illustrate common patterns for building knowledge graphs that solve many of today's pressing knowledge management problems. You'll quickly discover how these graphs become increasingly useful as you add data and augment them with algorithms and machine learning. Learn the organizing principles necessary to build a knowledge graph Explore how graph databases serve as a foundation for knowledge graphs Understand how to import structured and unstructured data into your graph Follow examples to build integration-and-search knowledge graphs Learn what pattern detection knowledge graphs help you accomplish Explore dependency knowledge graphs through examples Use examples of natural language knowledge graphs and chatbots Use graph algorithms and ML to gain insight into connected data.
  note: Jesús Barrasa and Jim Webber.
  note: Includes index.
  subject:
    topic: Graph theory
  subject:
    topic: Database management
  subject:
    topic: Semantic Web
  subject:
    topic: Data integration (Computer science)
  classification: QA166
  classification: 511.5
  related item:
    identifier: (OCoLC)1309066601
  identifier: 9781098127077
  identifier: 1098127072
  identifier: 1098127102
  identifier: 9781098127107
  identifier: 9781098127091 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 230626
    record change date: 20260130161903.7
    record identifier: in00004728271
    language of cataloging:
      language term: eng