Towards Reputation Enhanced Electronic Negotiations for Service Oriented Computing

König, S.; Hudert, Sebastian; Eymann, Torsten; Paolucci, Mario

doi:10.1007/978-3-540-92803-4_14

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…For example, when sellers submit bids, they may do so trying to incorporate reasoning about the trustworthiness of their competitors (as well as their view of their own trustworthiness). The work in [16] provides a comprehensive study on how to effectively use the information of sellers' trustworthiness to enhance the auctions. The work of Hazard and Singh [7] also provides some hints about how to discount buyer utility based on sellers' trustworthiness.…”

Section: Discussionmentioning

confidence: 99%

“…This performance can be measured by the false positive rate (FPR) and false negative rate (FNR [20] to measure the approaches' performance in detecting dishonest advisors. MCC is a convenient measure because it gives a single metric for the quality of binary classifications, and is computed as follows: (16) where = false position, = true positives, = false negatives, = true negatives. An MCC value is between -1 and +1.…”

Section: Performance Measurementmentioning

confidence: 99%

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Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems

Zhang

2011

J. theor. appl. electron. commer. res.

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The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation system. In this article, we first analyze the capabilities of existing approaches for coping with unfair ratings in different challenging scenarios, including ones where the majority of buyers are dishonest, buyers lack personal experience with sellers, sellers may vary their behavior, and buyers may provide a large number of ratings. We then present a personalized modeling approach (PMA) that has all these capabilities. Our approach allows a buyer to model both the private reputation and public reputation of other buyers to determine whether these buyers' ratings are fair. More importantly, in this work, we focus on experimental comparison of our approach with two key models in a simulated dynamic e-marketplace environment. We specifically examine the above mentioned scenarios to confirm our analysis and to demonstrate the capabilities of our approach. Our study thus provides the extensive experimental support for the personalized approach that can be effectively employed by reputation systems to cope with unfair ratings.

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Section: Discussionmentioning

confidence: 99%

Section: Performance Measurementmentioning

confidence: 99%

Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems

Zhang

2011

J. theor. appl. electron. commer. res.

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“…Most of the related work can be classified into the following three categories: (1) adaptive SLA mechanisms based on OWL, DAML-S and other semantic technologies [17,10,23]; (2) SLA based QoS systems, which consider varying service requirements but do not consider non matching SLA templates [1,20]; and (3) systems relying on the principles of autonomic computing [3,14,15].…”

Section: Related Workmentioning

confidence: 99%

“…König at al. investigate the trust issue in electronic negotiations, dealing with how to trust a potential transaction partner and how to choose such partners based on their past behavior [15].…”

Section: Related Workmentioning

confidence: 99%

VieSLAF Framework: Enabling Adaptive and Versatile SLA-Management

Brandić

Music

Leitner

et al. 2009

Lecture Notes in Computer Science

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Abstract. Novel computing paradigms like Grid and Cloud computing demand guarantees on non-functional requirements such as application execution time or price. Such requirements are usually negotiated following a specific Quality of Service (QoS) model and are expressed using Service Level Agreements (SLAs). Currently available QoS models assume either that service provider and consumer have matching SLA templates and common understanding of the negotiated terms or provide public templates, which can be downloaded and utilized by the end users. On the one hand, matching SLA templates represent an unrealistic assumption in systems where service consumer and provider meet dynamically and on demand. On the other hand, handling of public templates seems to be a rather challenging issue, especially if the templates do not reflect users' needs. In this paper we present VieSLAF, a novel framework for the specification and management of SLA mappings. Using VieSLAF users may specify, manage, and apply SLA mapping bridging the gap between non-matching SLA templates. Moreover, based on the predefined learning functions and considering accumulated SLA mappings, domain specific public SLA templates can be derived reflecting users' needs.

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