Trust in recommender systems

O’Donovan, John; Smyth, Barry

doi:10.1145/1040830.1040870

Cited by 665 publications

(419 citation statements)

References 9 publications

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“…In a paper entitled "Trust in recommender systems" [16], O'Donovan and Smyth propose algorithms for computing Profile Level Trust and Item Level Trust. Profile Level Trust is the percentage of correct recommendations that this producer has contributed.…”

Section: Related Workmentioning

confidence: 99%

Trust Metrics in Recommender Systems

Massa

Avesani²

2009

Human–Computer Interaction Series

110

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Section: Related Workmentioning

confidence: 99%

Trust Metrics in Recommender Systems

Massa

Avesani²

2009

Human–Computer Interaction Series

110

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“…This may be a valuable tool in social networks analysis [9], especially for scientific communities [17]. Another potential application of the proposed method is monitoring of knowledge dynamics based on the document's number of ranks as well as extension of various personalization systems with the collaborative trust [8,14,15].…”

Section: Discussionmentioning

confidence: 99%

Application of Agent-Based Personal Web of Trust to Local Document Ranking

Kopel

Kazienko

2007

Agent and Multi-Agent Systems: Technologies and Applications

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Abstract.Web is the boundless source of information and no one is able to process the vast amount of new documents published on the web every day, even with filtering out the documents the user is not interested in. However, most of the recent web documents are blog posts, news and other documents with the author information established. Each author who is also the receiver of web documents possesses their own personal agent that delivers trust information related to other authors as well as rank data for each new document. Trusts and ranks available for agents are exchanged between them and in this way new authors and new web documents can be easily assessed. Based on the general concept of Web of Trust the new idea of Personal Web of Trust and its application to local ranking method for web documents is proposed in the paper.

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“…According to [6], content-based and collaborative filtering are the more popular recommendation strategies. Collaborative filtering recommendations are motivated by the observation that we look for our acquaintances for recommendations.…”

Section: Overview Of Recommender Systemsmentioning

confidence: 99%

Document Recommender Agent Based on Hybrid Approach

Chekima¹,

On²,

Alfred³

et al. 2014

IJMLC

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Abstract-As Internet continues to grow, user tends to rely heavily on search engines. However, these search engines tend to generate a huge number of search results and potentially making it difficult for users to find the most relevant sites. This has resulted in search engines losing their usefulness. These users might be academicians who are searching for relevant academic papers within their interests. The need for a system that can assist in choosing the most relevant papers among the long list of results presented by search engines becomes crucial. In this paper, we propose Document Recommender Agent, that can recommend the most relevant papers based on the academician's interest. This recommender agent adopts a hybrid recommendation approach. In this paper we also show that recommendation based on the proposed hybrid approach is better that the content-based and the collaborative approaches.Index Terms-Document recommender agent, agent technology, information retrieval.

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Trust in recommender systems

Cited by 665 publications

References 9 publications

Trust Metrics in Recommender Systems

Trust Metrics in Recommender Systems

Application of Agent-Based Personal Web of Trust to Local Document Ranking

Document Recommender Agent Based on Hybrid Approach

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