Publications by Boi Faltings | EPFL Graph Search

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Because of the abundance of news on the web, news recommendation is an important problem. We compare three approaches for personalized news recommendation: collaborative filtering at the level of news items, content-based system recommending items with sim ...

An accurate model of the user's preferences is a crucial element of most decision support systems. It is often assumed that users have a well-defined and stable set of preferences that can be elicited through a set of questions. However, recent research ha ...

Many information systems are used in a problem solving context. Examples are travel planning systems, catalogs in electronic commerce, or agenda planning systems. They can be made more useful by integrating problem-solving capabilities into the information systems. This poses the challenge of scaleability: when hundreds of users access a server at the same time, it is important to avoid excessive computational load. We present the concept of SmartClients: lightweight problem-solving agents based on constrai

Many web sites collect reviews of products and services and use them provide rankings of their quality. However, such rankings are not personalized. We investigate how the information in the reviews written by a particular user can be used to personalize t ...

We present a multi-agent learning algorithm, ALMA-Learning, for efficient and fair allocations in large-scale systems. We circumvent the traditional pitfalls of multi-agent learning (e.g., the moving target problem, the curse of dimensionality, or the need ...

In this paper we create a model of human behavior in online communities, based on the network topology and on the communication content. The model contains eleven distinct hypotheses, which validate three intuitions. The rst intuition is that the network t ...

Ontologies are being successfully used to overcome semantic heterogeneity, and are becoming fundamental elements of the Semantic Web. Recently, it has also been shown that ontologies can be used to build more accurate and more personalized recommendation s ...

To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due to a lack of inductive bias in the learning methods used to build the prediction mode ...

Conditional dichotomy, the contrast between two outputs conditioned on the same context, is vital for applications such as debate, defeasible natural language inference, and causal reasoning. Existing methods that rely on semantic similarity often fail to capture the nuanced oppositional dynamics essential for these applications. Motivated by these limitations, we introduce a novel task, Conditional Dichotomy Quantification (ConDQ), which formalizes the direct measurement of conditional dichotomy and provid

This paper outlines a vision for community-driven sensing of our environment. At its core, community sensing is a dynamic new form of mobile geosensor network. We believe that community sensing networks, in order to be widely deployable and sustainable, ne ...

Language models (LMs) have recently shown remarkable performance on reasoning tasks by explicitly generating intermediate inferences, e.g., chain-of-thought prompting. However, these intermediate inference steps may be in- appropriate deductions from the i ...

Reputation mechanisms offer an efficient way of building the necessary level of trust in electronic markets. In the absence of independent verification authorities that can reveal the true outcome of a ransaction, market designers have to insure that it is in the best interest of the trading agents to report the behavior in transactions truthfully. As opposed to side-payment schemes that correlate a present report with future reports submitted about the same agent, we present a mechanism that discovers (in

In this paper we deal with the problem of optimally placing a set of query operators in an overlay network. Each user is interested in performing a query on streaming data and each query has an associated set of in-network operators that filter, aggregate and process the data in various ways. Each user has private information about the operators associated with a query and about the utility from different combinations of operator placements. Each server in the overlay network is able to perform some set of

We present a human computation game based on the popular board game - Dixit. We ask the players not only for annotations, but for a direct critique of the result of an automated system.We present the results of the initial run of the game, in which the answers of 15 players were used to profile the mistakes of an aspect-based opinion mining system. We show that the gameplay allowed us to identify the major faults of the extracted opinions. The players' actions thus helped improve the opinion extraction algo

Distributed Constraint Optimization (DCOP) is a field that has recently been getting more and more attention from academia and industry. However, very few open-source, off-the-shelf tools are currently available to solve DCOPs; examples are FRODO, DisChoco and DCOPolis. A DCOP platform should possess the following key qualities: the framework should be reliable and extensively tested, deployable in a truly distributed setting, and modular so that it is easy to customize and extend. This poster presents the

Currently known methods for robot planning fall far behind human capabilities: they require approximations of shapes, and they cannot generate plans which involve moving obstacles to clear a path for the moving object. In this paper, we explore the hypothesis that means-ends analysis based on a world model involving mental imagery allows more human-like solutions. Our method is based on a novel way of representing planning constraints which makes it possible to incrementally generate the symbolic representa

Distributed constraint optimization (DCOP) provides a framework for coordinated decision making by a team of agents. Often, during the decision making, capacity constraints on agents' resource consumption must be taken into account. To address such scenari ...

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 ...

Preference-based search is the problem of finding an item that matches best with a user's preferences. User studies show that example-based tools for preference-based search can achieve significantly higher accuracy when they are complemented with suggestions chosen to inform users about the available choices. We present {\tt FlatFinder}, an implementation of an example-based tool and discuss how such a tool as well as suggestions can be efficiently implemented even for large product databases.

Networked computing environments are subject to configuration errors, unauthorized users, undesired activities and attacks by malicious software. These can be detected by monitoring network traffic, but network administrators are overwhelmed by the amount ...

Boi Faltings

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Personalized news recommendation based on collaborative filtering

Agile preference models based on soft constraints

SmartClients: Constraint satisfaction as a paradigm for scaleable intelligent information systems

Recommendation using textual opinions

Improving Multi-agent Coordination by Learning to Estimate Contention

A Model of Online Social Interactions based on Sentiment Analysis and Content Similarity

Using Hierarchical Clustering for Learning the Ontologies used in Recommendation Systems

Overcoming Incomplete User Models in Recommendation Systems Via an Ontology

Conditional Dichotomy Quantification via Geometric Embedding

OpenSense: open community driven sensing of environment

REFINER: Reasoning Feedback on Intermediate Representations

Truthful Reputation Information in Electronic Markets without Independent Verification

Optimizing Streaming Applications with Self-Interested Users using MDPOP

A Novel Human Computation Game for Critique Aggregation

FRODO: An Open-Source Framework for Distributed Constraint Optimization

Applying Means-Ends Analysis to Spatial Planning

Distributed Constraint Optimization with Structured Resource Constraints

User Profiling Using Submitted Review Content

Design and Implementation of Preference-based Search

Hypergraph Clustering for Better Network Traffic Inspection