A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.
Original languageEnglish
Pages (from-to)97-123
Number of pages27
JournalJOURNAL OF WEB ENGINEERING
Volume18
Issue number1-3
DOIs
Publication statusPublished - Jan 2019

Keywords

  • Hybrid systems
  • neurosymbolic systems
  • knowledge representation
  • machine learning
  • design patters

Cite this

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title = "A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems",
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A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems. / van Harmelen, Frank; ten Teije, Annette.

In: JOURNAL OF WEB ENGINEERING, Vol. 18, No. 1-3, 01.2019, p. 97-123.

Research output: Contribution to JournalArticleAcademicpeer-review

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