کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
350723 618455 2014 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Empowering the access to public procurement opportunities by means of linking controlled vocabularies. A case study of Product Scheme Classifications in the European e-Procurement sector
ترجمه فارسی عنوان
توانایی دسترسی به فرصت های خرید عمومی با استفاده از ارتباط واژگان کنترل شده. مطالعه موردی طبقه بندی محصولات طرح در بخش تدارکات الکترونیکی در اروپا
کلمات کلیدی
تدارکات الکترونیکی، طبقه بندی محصولات طرح، داده های باز شده مرتبط است وب معنایی، سیستم های خبره
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• We promote to the Linked Data initiative the main Product Scheme Classifications.
• We demonstrate how Linked Data improves the access to information and data.
• We apply the results to the European e-Procurement domain.
• We implement a system to recommend CPV 2008 codes to expert users.

The present paper introduces a method to promote existing controlled vocabularies to the Linked Data initiative. A common data model and an enclosed conversion method for knowledge organization systems based on semantic web technologies and vocabularies such as SKOS are presented. This method is applied to well-known taxonomies and controlled vocabularies in the business sector, more specifically to Product Scheme Classifications created by governmental institutions such as the European Union or the United Nations. Since these product schemes are available in a common and shared data model, the needs of the European e-Procurement sector are outlined to finally demonstrate how Linked Data can address some of the challenges for publishing and retrieving information resources. As a consequence, two experiments are also provided in order to validate the gain, in terms of expressivity, and the exploitation of this emerging approach to help both expert and end-users to make decisions on the selection of descriptors for public procurement notices.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Human Behavior - Volume 30, January 2014, Pages 674–688
نویسندگان
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