Learning design knowledge as generalization

Heng Li, Xindong Wu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Generalizing design knowledge is a process of extracting knowledge from design-provideddata. Although it is one of the most common waysof “learning” design knowledge, generalizationhas a fundamental weakness: except for special occasions, the results of generalization can never be validated. Inquiries into generalization have therefore dealt with questions ofwhat are the best criteria for guiding the generalization. This paper argues that generalizing design knowledge involves three essential tasks; knowledge representation, a description languagefor design examples, and generalization operators. An application of generalizing empirical networks from design examples is described to illustrate these three tasks in the development of a generalization system.
Original languageEnglish
Pages (from-to)181-207
Number of pages27
JournalCybernetics and Systems
Volume29
Issue number2
DOIs
Publication statusPublished - 1 Jan 1998

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Artificial Intelligence

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