Knowledge discovery in inspection reports of marine structures

被引:7
作者
Lee, Seung-Kyung [1 ]
Kim, Bongseok [1 ]
Huh, Minhoe [1 ]
Park, Jooseoung [1 ]
Kang, Seokho [1 ]
Cho, Sungzoon [1 ]
Lee, Dongha [2 ]
Lee, Daehyung [2 ]
机构
[1] Seoul Natl Univ, Dept Ind Engn, Seoul 151744, South Korea
[2] Daewoo Shipbldg & Marine Engn Co Ltd, Cent R&D Inst, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Knowledge Discovery in Textual Databases; Text mining; Shipbuilding and marine engineering industry; Inspection process; TEXT CLASSIFICATION; WEBSOM;
D O I
10.1016/j.eswa.2013.07.109
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1153 / 1167
页数:15
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