کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4911249 | 1428283 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Retrieving similar cases for construction project risk management using Natural Language Processing techniques
ترجمه فارسی عنوان
گرفتن موارد مشابه برای مدیریت ریسک پروژه ساخت و ساز با استفاده از تکنیک های پردازش زبان طبیعی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
چکیده انگلیسی
Case-based reasoning (CBR) is an important approach in construction project risk management. It emphasises that previous knowledge and experience of accidents and risks are highly valuable and could contribute to avoiding similar risks in new situations. In the CBR cycle, retrieving useful information is the first and the most important step. To facilitate the CBR for practical use, some researchers and organisations have established construction accident databases and their size is growing. However, as those documents are written in everyday language using different ways of expression, how information in similar cases is retrieved quickly and accurately from the database is still a huge challenge. In order to improve the efficiency and performance of risk case retrieval, this paper proposes an approach of combining the use of two Natural Language Processing (NLP) techniques, i.e. Vector Space Model (VSM) and semantic query expansion, and outlines a framework for this Risk Case Retrieval System. A prototype system is developed using the Python programming language to support the implementation of the proposed method. Preliminary test results show that the proposed system is capable of retrieving similar cases automatically and returning, for example, the top 10 similar cases.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automation in Construction - Volume 80, August 2017, Pages 66-76
Journal: Automation in Construction - Volume 80, August 2017, Pages 66-76
نویسندگان
Yang Zou, Arto Kiviniemi, Stephen W. Jones,