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Boi Faltings

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Related publications (166)

Predicting Online Performance of News Recommender Systems Through Richer Evaluation Metrics

Boi Faltings, Florent Frédéric Garcin, Andrii Maksai

We investigate how metrics that can be measured offline can be used to predict the online performance of recommender systems, thus avoiding costly A-B testing. In addition to accuracy metrics, we combine diversity, coverage, and serendipity metrics to crea ...

2015

Incentivizing Truthful Responses with the Logarithmic Peer Truth Serum

Boi Faltings, Goran Radanovic

We consider a participatory sensing scenario where a group of private sensors observes the same phenomenon, such as air pollution. We design a novel payment mechanism that incentivizes participation and honest behavior using the peer prediction approach, i ...

2015

Incentive Schemes for Participatory Sensing

Boi Faltings, Goran Radanovic

We consider a participatory sensing scenario where a group of private sensors observes the same phenomenon, such as air pollution. Since sensors need to be installed and maintained, owners of sensors are inclined to provide inaccurate or random data. We de ...

2015

Recommendation Strategy Portfolios

Boi Faltings, Claudiu-Cristian Musat

A recommender system comprising at least one computing device which comprises one or more processors and one or more computer-readable storage media operatively coupled to at least one of the processors, wherein said computing device performs a method of a ...

2015

Incentives for Subjective Evaluations with Private Beliefs

Boi Faltings, Goran Radanovic

The modern web critically depends on aggregation of information from self-interested agents, for example opinion polls, product ratings, or crowdsourcing. We consider a setting where multiple objects (questions, products, tasks) are evaluated by a group of ...

2015

A Region-Based Model for Estimating Urban Air Pollution

Boi Faltings, Arnaud Jutzeler, Jingshi Li

2014

Acquiring Commonsense Knowledge for Sentiment Analysis through Human Computation

Boi Faltings, Marina Boia, Claudiu-Cristian Musat

2014

Incentives for Truthful Information Elicitation of Continuous Signals

Boi Faltings, 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. We propose a novel mechanism that elicits both private signals ...

2014

User Profiling Using Submitted Review Content

Boi Faltings, Yizhong Liang, Claudiu-Cristian Musat

A computer-implemented method for generating a user profile of a user of an online platform, a computer-implemented method for providing a first user with targeted information and a computer-implemented method for providing a user of an online platform wit ...

2014

Symmetric Subgame-Perfect Equilibria in Resource Allocation

Boi Faltings, Ludek Cigler

We analyze symmetric protocols to rationally coordinate on an asymmetric, efficient allocation in an infinitely repeated N-agent, C-resource allocation problems, where the resources are all homogeneous. Bhaskar proposed one way to achieve this in 2-agent, ...

AI Access Foundation2014

Constructing Context-Aware Sentiment Lexicons with an Asynchronous Game with a Purpose

Boi Faltings, Marina Boia, Claudiu-Cristian Musat

One of the reasons sentiment lexicons do not reach human-level performance is that they lack the contexts that define the polarities of words. While obtaining this knowledge through machine learning would require huge amounts of data, context is commonsens ...

Springer-Verlag Berlin2014

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

Multi-Objective Quality-Driven Service Selection-A Fully Polynomial Time Approximation Scheme

Boi Faltings, Immanuel Trummer

The goal of multi-objective quality-driven service selection (QDSS) is to find service selections for a workflow whose quality-of-service (QoS) values are Pareto-optimal. We consider multiple QoS attributes such as response time, cost, and reliability. A s ...

Institute of Electrical and Electronics Engineers2014

Protecting Privacy through Distributed Computation in Multi-agent Decision Making

Boi Faltings, Thomas Léauté

As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and distributed com ...

AI Access Foundation2013

Using Incentives to Obtain Truthful Information

Boi Faltings

There are many scenarios where we would like agents to report their observations or expertise in a truthful way. Game-theoretic principles can be used to provide incentives to do so. I survey several approaches to eliciting truthful information, in particu ...

2013

A Robust Bayesian Truth Serum for Non-binary Signals

Boi Faltings, Goran Radanovic

Several mechanisms have been proposed for incentivizing truthful reports of a private signals owned by rational agents, among them the peer prediction method and the Bayesian truth serum. The robust Bayesian truth serum (RBTS) for small populations and bin ...

2013

PEN recsys: a Personalized News Recommender Systems Framework (DEMO)

Boi Faltings, Florent Frédéric Garcin

We present the Personalized News (PEN) recommender systems framework, (Note that this paper is an extended abstract of Garcin2013b), currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its sy ...

2013

Decentralized Anti-coordination Through Multi-agent Learning

Boi Faltings, Ludek Cigler

To achieve an optimal outcome in many situations, agents need to choose distinct actions from one another. This is the case notably in many resource allocation problems, where a single resource can only be used by one agent at a time. How shall a designer ...

AI Access Foundation2013

Personalized News Recommendation with Context Trees

Boi Faltings, Florent Frédéric Garcin, Christos Dimitrakakis

The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...

2013

PEN recsys: a Personalized News Recommender Systems Framework

Boi Faltings, Florent Frédéric Garcin

We present the Personalized News (PEN) recommender systems framework, currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its system architecture and related components. We show how a researc ...

2013

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