کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
382883 660796 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A knowledge extraction and representation system for narrative analysis in the construction industry
ترجمه فارسی عنوان
سیستم استخراج دانش و نمایندگی برای تحلیل روایت در صنعت ساخت و ساز
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A knowledge extraction and representation system for narrative analysis is presented.
• The system semi-automatically processes narrative analysis and generates narrative maps from raw narrative texts.
• A prototype was successfully implemented in a reference site in the construction industry.
• Domain experts agree that the system can effectively represent narrative elements and flows.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 13, 1 October 2014, Pages 5710–5722
نویسندگان
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