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On the Use of Self-Organizing Map for Text Clustering in Engineering Change Process Analysis: A Case Study
المؤلفون المشاركون
Pacella, Massimo
Grieco, Antonio
Blaco, Marzia
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-12-04
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
In modern industry, the development of complex products involves engineering changes that frequently require redesigning or altering the products or their components.
In an engineering change process, engineering change requests (ECRs) are documents (forms) with parts written in natural language describing a suggested enhancement or a problem with a product or a component.
ECRs initiate the change process and promote discussions within an organization to help to determine the impact of a change and the best possible solution.
Although ECRs can contain important details, that is, recurring problems or examples of good practice repeated across a number of projects, they are often stored but not consulted, missing important opportunities to learn from previous projects.
This paper explores the use of Self-Organizing Map (SOM) to the problem of unsupervised clustering of ECR texts.
A case study is presented in which ECRs collected during the engineering change process of a railways industry are analyzed.
The results show that SOM text clustering has a good potential to improve overall knowledge reuse and exploitation.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Pacella, Massimo& Grieco, Antonio& Blaco, Marzia. 2016. On the Use of Self-Organizing Map for Text Clustering in Engineering Change Process Analysis: A Case Study. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099695
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Pacella, Massimo…[et al.]. On the Use of Self-Organizing Map for Text Clustering in Engineering Change Process Analysis: A Case Study. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1099695
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Pacella, Massimo& Grieco, Antonio& Blaco, Marzia. On the Use of Self-Organizing Map for Text Clustering in Engineering Change Process Analysis: A Case Study. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099695
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099695
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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