Title of article :
Knowledge discovery in inspection reports of marine structures
Author/Authors :
Lee، نويسنده , , Seung-kyung and Kim، نويسنده , , Bongseok and Huh، نويسنده , , Minhoe and Park، نويسنده , , Jooseoung and Kang، نويسنده , , Seokho and Cho، نويسنده , , Sungzoon and Lee، نويسنده , , Dongha and Lee، نويسنده , , Daehyung، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Abstract :
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.
Keywords :
Knowledge Discovery in Textual Databases , Text Mining , Shipbuilding and marine engineering industry , Inspection process
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications