Publications by Radu Jurca | EPFL Graph Search

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Incentives for Effort in Crowdsourcing using the Peer Truth Serum

Boi Faltings, Radu Jurca, Goran Radanovic

Crowdsourcing is widely proposed as a method to solve large variety of judgement tasks, such as classifying website content, peer grading in online courses, or collecting real-world data. As the data reported by workers cannot be verified, there is a tende ...

Assoc Computing Machinery2016

Eliciting Truthful Information with the Peer Truth Serum

Boi Faltings, Radu Jurca, Goran Radanovic

We consider settings where a collective intelligence is formed by aggregating information contributed from many independent agents, such as product reviews, community sensing or opinion polls. To encourage participation and avoid selection bias, agents sho ...

2014

Incentive Mechanisms for Community Sensing

Boi Faltings, Radu Jurca, Jingshi Li

Sensing and monitoring of our natural environment are important for sustainability. As sensor systems grow to a large scale, it will become infeasible to place all sensors under centralized control. We investigate community sensing, where sensors are contr ...

Ieee Computer Soc2014

Eliciting Truthful Measurements from a Community of Sensors

Boi Faltings, Radu Jurca, Jingshi Li

As the Internet of Things grows to large scale, its components will increasingly be controlled by selfinterested agents. For example, sensor networks will evolve to community sensing where a community of agents combine their data into a single coherent str ...

2012

Reporting incentives and biases in online review forums

Boi Faltings, Radu Jurca, Florent Frédéric Garcin

Online reviews have become increasingly popular as a way to judge the quality of various products and services. However, recent work demonstrates that the absence of reporting incentives leads to a biased set of reviews that may not reflect the true qualit ...

2010

Rating aggregation in collaborative filtering systems

Boi Faltings, Radu Jurca, Florent Frédéric Garcin, Nadine Joswig

Recommender systems based on user feedback rank items by aggregating users' ratings in order to select those that are ranked highest. Ratings are usually aggregated using a weighted arithmetic mean. However, the mean is quite sensitive to outliers and bias ...

ACM Press2009

Aggregating Reputation Feedback

Boi Faltings, Radu Jurca, Florent Frédéric Garcin

A fundamental task in reputation systems is to aggregate multiple feedback ratings into a single value that can be used to compare the reputation of different entities. Feedback is most commonly aggregated using the arithmetic mean. However, the mean is qu ...

2009

Mechanisms for Making Crowds Truthful

Boi Faltings, Radu Jurca

We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a product or service s ...

AI Access Foundation2009

Radu Jurca

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Incentives for Effort in Crowdsourcing using the Peer Truth Serum

Eliciting Truthful Information with the Peer Truth Serum

Incentive Mechanisms for Community Sensing

Eliciting Truthful Measurements from a Community of Sensors

Incentives for Answering Hypothetical Questions

Reporting incentives and biases in online review forums

Rating aggregation in collaborative filtering systems

Aggregating Reputation Feedback

Mechanisms for Making Crowds Truthful

System and method for monitoring quality of service

Reporting incentives and biases in online review forums

Incentives for Effort in Crowdsourcing using the Peer Truth Serum

Eliciting Truthful Information with the Peer Truth Serum

Incentive Mechanisms for Community Sensing

Eliciting Truthful Measurements from a Community of Sensors

Incentives for Answering Hypothetical Questions

Rating aggregation in collaborative filtering systems

Aggregating Reputation Feedback

Mechanisms for Making Crowds Truthful

System and method for monitoring quality of service