A knowledge extraction and representation system for narrative analysis in the construction industry

C. L. Yeung, Chi Fai Cheung, W. M. Wang, Yue Hong Eric Tsui

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)

Abstract

Many researchers advocate that the real-world narratives shared by experts or knowledge workers are helpful in teaching and educating novices to learn new knowledge and skills. Narrative analysis is a useful method for experts to understand narratives. However, it does not produce any clear or explicit layouts. This is not easy for a new learner without prior knowledge to glean the right messages from narratives within a short time. In this paper, a narrative knowledge extraction and representation system (NKERS) is presented to extract and represent narrative knowledge in an effective manner. The NKERS is composed of a narrative knowledge element extraction algorithm, a narrative knowledge representation method and a narrative knowledge database. A prototype system has been built and trial implemented in the construction industry. The results show that the domain experts agree that the narrative maps generated by the NKERS can effectively represent narrative elements and flows. Three-quarters of respondents expressed that they will use the produced narrative maps in their training courses to facilitate students' learning.
Original languageEnglish
Pages (from-to)5710-5722
Number of pages13
JournalExpert Systems with Applications
Volume41
Issue number13
DOIs
Publication statusPublished - 1 Oct 2014

Keywords

  • Construction industry
  • Knowledge extraction
  • Knowledge management
  • Knowledge representation
  • Narrative analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Engineering(all)

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