دانلود مقاله ISI انگلیسی شماره 47216
ترجمه فارسی عنوان مقاله

یک بستر آزمایشی شبیه سازی برای تجزیه و تحلیل مکانیزم اعتماد و اعتبار در بازارهای آنلاین غیر قابل اعتماد

عنوان انگلیسی
A simulation testbed for analyzing trust and reputation mechanisms in unreliable online markets
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
47216 2014 19 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Electronic Commerce Research and Applications, Volume 13, Issue 5, September–October 2014, Pages 368–386

ترجمه کلمات کلیدی
اعتماد و اعتبار - باز کردن بازارهای آنلاین - بستر آزمایشی شبیه سازی - مدل سازی عامل
کلمات کلیدی انگلیسی
Trust and reputation; Open online markets; Simulation testbed; Agent modeling
پیش نمایش مقاله
پیش نمایش مقاله  یک بستر آزمایشی شبیه سازی برای تجزیه و تحلیل مکانیزم اعتماد و اعتبار در بازارهای آنلاین غیر قابل اعتماد

چکیده انگلیسی

Modern online markets are becoming extremely dynamic, indirectly dictating the need for (semi-) autonomous approaches for constant monitoring and immediate action in order to satisfy one’s needs/preferences. In such open and versatile environments, software agents may be considered as a suitable metaphor for dealing with the increasing complexity of the problem. Additionally, trust and reputation have been recognized as key issues in online markets and many researchers have, in different perspectives, surveyed the related notions, mechanisms and models. Within the context of this work we present an adaptable, multivariate agent testbed for the simulation of open online markets and the study of various factors affecting the quality of the service consumed. This testbed, which we call Euphemus, is highly parameterized and can be easily customized to suit a particular application domain. It allows for building various market scenarios and analyzing interesting properties of e-commerce environments from a trust perspective. The architecture of Euphemus is presented and a number of well-known trust and reputation models are built with Euphemus, in order to show how the testbed can be used to apply and adapt models. Extensive experimentation has been performed in order to show how models behave in unreliable online markets, results are discussed and interesting conclusions are drawn.