کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
386790 660891 2014 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Knowledge discovery in inspection reports of marine structures
ترجمه فارسی عنوان
کشف دانش در گزارش بازرسی سازه های دریایی
کلمات کلیدی
کشف دانش در پایگاه داده های متنی، استخراج متن، صنعت کشتی سازی و مهندسی دریایی، پروسه بازرسی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• Inspection reports are free-form texts for defects on marine structures.
• We applied KDT process for understanding the “what” and “where” of defects.
• Particularly, we proposed a concept extraction and linkage as an add-on for SOM.
• It derives and visualizes a concept graph as a snapshot outlining defect-types.
• It helps domain experts better understand and systematically respond to defects.

Inspection reports, commonly called “punches” in the marine structuring domain, are written documents about defects or supplementations on marine structures. Analyzing the inspection reports improves the construction process for the structure and prevents additional “punches.” This consequently reduces construction delays and supplementary costs. The free-form texts of the reports, however, hinder management from understanding the nature of defects. Therefore, we applied Knowledge Discovery in the Textual Databases (KDT) process to answer the questions, “what kinds of defects are reported while inspecting a marine structure, and which of them are closely related?” In particular, we propose a concept extraction and linkage approach as an “add-on” module for the Self-Organizing Map (SOM), a clustering algorithm for document organization. A purely data-driven graph is derived for defect-types, which gives it in an easy-to-understand form for domain experts and reduces the gap between data analysis and its practical use. Interpretation with domain experts showed that our KDT process is useful in understanding the nature of defects in the domain and systematically responding to some other related defects.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 4, Part 1, March 2014, Pages 1153–1167
نویسندگان
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