---
title: "Trust No One: Evaluating Trust-based Filtering for Recommenders"
authors:
  - "John O'Donovan"
  - "Barry Smyth"
doi: ""
url: "https://ijcai.org/proceedings/2005/321"
pdf: "https://ijcai.org/proceedings/2005/0321.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "1663-1664"
track: ""
keywords:
---

# Trust No One: Evaluating Trust-based Filtering for Recommenders

John O'Donovan, Barry Smyth

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 1663-1664.

## Abstract

To be successful recommender systems must gain the trust of users. To do this they must demonstrate their ability to make reliable predictions. We argue that collaborative filtering recommendation algorithms can benefit from explicit models of trust to inform their predictions. We present one such model of trust along with a cost-benefit analysis that focuses on the classical trade-off that exists between recommendation coverage and prediction accuracy.