A Normal-Distribution Based Reputation Model

Abdel-Hafez, Ahmad; Xu, Yan; Jøsang, Audun

doi:10.1007/978-3-319-09770-1_13

Cited by 12 publications

(5 citation statements)

References 10 publications

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“…Abdel-Hafez et al [21] used the normal-distribution to generate weighted average reputation model which explicitly reflects the distribution of ratings of items. Their proposed Normal Distribution based Reputation with Uncertainty (NDRU) model is described as a weighted average method where the weights reflect the distribution of ratings in the overall score.…”

Section: Related Workmentioning

confidence: 99%

Item Reputation-Aware Recommender Systems

Abdel-Hafez

Tian

2014

Proceedings of the 16th International Conference on Information Integration and Web-Based Applications &Amp; Services

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Recommender systems provide personalized advice for online customers based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems employ users' ratings to generate their output. In this paper, we aim to combine reputation models with recommender systems to enhance the accuracy of recommendations. Our proposed methods make two contributions. First of all, we propose two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively. In addition, a novel personalized reputation method is designed in order to generate item reputations based upon users' interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems.

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Section: Related Workmentioning

confidence: 99%

Item Reputation-Aware Recommender Systems

Abdel-Hafez

Tian

2014

Proceedings of the 16th International Conference on Information Integration and Web-Based Applications &Amp; Services

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“…Another reputation structure utilized by researchers is based on Normal Distribution Reputation(NDR) [41], irrespective of the domain various reputation models have been widely been researched and utilized in online market places, p2p systems for example eigentrust [42], regret [43]. It is worth mentioning that Bayesian reputation systems, addressed the limitations of the most popular eigen reputation systems [44].…”

Section: B Reputation Systemsmentioning

confidence: 99%

Reputation-Based Approach Toward Web Content Credibility Analysis

et al. 2019

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Web content credibility implies finding credible and correct information on the web. Recent studies have shown there is an increasing trend of users turning towards the web for searching information related to a variety of topics including health, stocks, education, politics to name few. Information credibility is a critical factor in these domains for the decision makers. There is no limitation on the authorship of those articles and content. One criterion for evaluating credibility is to check the authority or source of information. However, there are situations when wrong information flows from credible sources. There are various approaches towards credibility assessment, broadly categorized into human-based and computational approaches. Computational approaches utilizing machine learning based techniques are computationally expensive. Reputation based approaches overcome this, however the latest work fails to take into account issue of negative referrals and utilizes simple summation as the calculation structure making it more resilient to attacks. This paper put forth verified hypothesis of direct relationship of credibility to the expertise of entity. Authors proposed a Bayesian based approach using feedback in the form of interaction among the entities to compute their expertise level, thereby showing improved results in terms of Precision, Correlation and Mean Average Error. The experiments are performed on two different datasets, one of the dataset is developed from a survey as the part of the research study. The results from the two experiments show that the reputation ranks are independent of the pattern of ratings and density of data, unlike previous techniques whose results were limited by these factors. The proposed technique gives 27% and 18% more precise results for the two experiments respectively compared to the baseline. The correlation results are also significant in both experiments for the proposed technique with significant values of 0.39 and 0.87 showing a linear relationship between predicted and original data. The paper also discusses the reputation attacks and proposes counter measures to tackle these attacks through simulation results.INDEX TERMS Web content credibility, information ranking, reputation systems, experts ranking.

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“…The weight can represent the user's reputation score, the time when the rating was given, or the distance between the current reputation score and the rating received [6,7]. Abdel-Hafez et al [20,21] used the normal-distribution to generate weighted average reputation model which explicitly reflects the distribution of ratings of items.…”

Section: Related Workmentioning

confidence: 99%

A Reputation-Enhanced Recommender System

Abdel-Hafez

Tang

Tian

et al. 2014

Advanced Data Mining and Applications

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Abstract. Reputation systems are employed to provide users with advice on the quality of items on the Web, based on the aggregated value of user-based ratings. Recommender systems are used online to suggest items to users according to the users, expressed preferences. Yet, recommender systems will endorse an item regardless of its reputation value. In this paper, we report the incorporation of reputation models into recommender systems to enhance the accuracy of recommendations. The proposed method separates the implementation of recommender and reputation systems for generality. Our experiment showed that the proposed method could enhance the accuracy of existing recommender systems.

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A Normal-Distribution Based Reputation Model

Cited by 12 publications

References 10 publications

Item Reputation-Aware Recommender Systems

Item Reputation-Aware Recommender Systems

Reputation-Based Approach Toward Web Content Credibility Analysis

A Reputation-Enhanced Recommender System

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