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An interval type-2 fuzzy logic based framework for reputation management in Peer-to-Peer e-commerce

机译:对等电子商务中基于区间2模糊逻辑的信誉管理框架

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摘要

© 2015 Elsevier Inc. During the last two decades, the Internet has changed people's habits and improved their daily life activities and services. In particular, the emergence of e-commerce provided manufactures and vendors with more business opportunities. This allowed customers to benefit from a global, quicker and cheaper shopping environment. However, e-commerce is evolving from a centralised approach, where consumers directly purchase products and services from businesses, to a Peer-to-Peer (P2P) perspective, in which customers buy and sell goods amongst themselves. In P2P scenarios, it is crucial to protect both buyers and sellers (the peers) from being victimised by possible fraud arising from the uncertainties, vagueness and ambiguities that characterise the interactions amongst unknown business entities. For this reason, the so-called reputation models are becoming a key architectural component of any e-commerce portal. These systems are intended to evaluate the basic features of each entity (buyer, seller, goods, etc.) involved in a given trading transaction in order to assess the trust level of the given transaction and minimise fraud. However, in spite of their wide deployment, the reputation models need to be enhanced to handle the various sources of uncertainties in order to produce more accurate outputs which will allow to increase the trust and decrease the fraud levels within e-commerce systems. In this paper, we present an interval type-2 fuzzy logic based framework for reputation management in (P2P) e-commerce which is capable of better handling the faced uncertainties. We have carried out various experiments based on eBay ® -like transaction datasets which have shown that the proposed type-2 fuzzy logic based system can provide better performance (in terms of malicious peer detection and exchanged message overhead) when compared to the other well-known and heavily used approaches like the eBay ® approach, EigenTrust, PeerTrust as well as the type-1 fuzzy based counterpart approach.
机译:©2015 Elsevier Inc.在过去的二十年中,互联网改变了人们的习惯,并改善了他们的日常生活活动和服务。特别是,电子商务的出现为制造商和销售商提供了更多的商机。这使客户可以受益于全球,更快,更便宜的购物环境。但是,电子商务正在从一种集中的方法(从消费者直接从企业购买产品和服务)到点对点(P2P)的角度发展,在这种方法中,客户之间可以买卖商品。在P2P场景中,至关重要的是保护买卖双方(同行)免受可能因未知业务实体之间交互的不确定性,模糊性和歧义性造成的欺诈的影响。由于这个原因,所谓的信誉模型正成为任何电子商务门户的关键体系结构组件。这些系统旨在评估涉及给定交易交易的每个实体(买方,卖方,商品等)的基本特征,以便评估给定交易的信任度并最大程度地减少欺诈。但是,尽管部署了广泛的信誉模型,但仍需要增强信誉模型以处理各种不确定性源,以便产生更准确的输出,这将有助于增加信任度并降低电子商务系统内的欺诈水平。在本文中,我们提出了一种基于间隔2型模糊逻辑的(P2P)电子商务信誉管理框架,该框架能够更好地处理面临的不确定性。我们已经基于类似eBay®的交易数据集进行了各种实验,这些实验表明,与其他类型的交易记录相比,拟议的基于2型模糊逻辑的系统可以提供更好的性能(在恶意对等检测和交换消息开销方面)。已知且使用频繁的方法,例如eBay®方法,EigenTrust,PeerTrust以及基于类型1的模糊对等方法。

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