PEN recsys: a Personalized News Recommender Systems Framework

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 researcher can easily evaluate different algorithms thanks to a web-based interface. Finally, we discuss important factors to take into account when conducting online evaluation, and report on our experience when deploying recommendations on a live-traffic website

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

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 system architecture and related components. We show how a researcher can easily evaluate different algorithms thanks to a web-based interface

The snow avalanches risk on Alpine roads network

Road accessibility is highly strategic for the maintenance of economic activities but also for the emergency services. In mountains, snow avalanches are a particularly strong threat because, in addition to the victims and direct damage, they cause a loss of accessibility more or less prolonged when the networks are already strongly altered by seasonal closures. Specifically, risk to traffic roads caused by snow avalanches has been very rarely assessed at a regional scale. To assess the physical, human and functional vulnerabilities of road networks in three Alpine departments (Alpes-de-Haute-Provence, Hautes-Alpes, Alpes-Maritimes), the first step of this research was to geo-locate and harmonize within a GIS all information sources about the consequences of avalanches on roads. This allowed identifying the road impacts of avalanches since 1937, to characterize the intensity and typology of damages and to evaluate the functional vulnerability of networks. The second step was to produce simple risk indexes of dysfunction and isolation at this regional scale. These indicators were modeled using the graph theory in a GIS framework, integrating avalanche activity indicators derived from the past activity with the road network. The obtained output maps should facilitate the decision support for crisis management and a comparative spatial analysis at the regional scale

Aggregating information from the crowd:ratings, recommendations and predictions

With an ever-growing amount of data generated on the web, aggregating information from the crowd into meaningful knowledge has become crucial to companies in order to create a competitive edge. Not only companies, but also organizations and governments can benefit from this aggregation. In this thesis, we illustrate the benefits of aggregating information from the crowd with three applications. In the first application, we investigate different ways of aggregating users’ ratings on review websites. With the help of gamification techniques, we introduce a new methodology for studying users’ rating behaviour, and show that there is a balance between the amount of private information elicited from the crowd and the accuracy of the aggregated rating. In the second application, we consider the aggregation of implicit feedbacks from the crowd in order to generate personalized recommendations of news articles. We propose a new class of recommender systems based on Context Trees (CT), specifically designed for a dynamic domain like the news. We show that CT recommender systems generate accurate and novel recommendations in an offline setting, but also in real time on the newspaper website swissinfo.ch. In the last application, we address the problem of eliciting private information to predict outcomes of events. We report on an experimental platform called swissnoise that allows users to express their opinions on various topics ranging from sports to politics. It is the first platformto implement a peer prediction mechanism for online opinion polls. We show that peer prediction can be practically implemented, and discuss the design choices and variations made to such mechanism. Finally, we find that peer prediction achieves a performance comparable to that of prediction market

Pneumonies acquises sous ventilation mécanique (surmortalité des patients recevant une antibiothérapie probabiliste inadéquate)

AIX-MARSEILLE2-BU Méd/Odontol. (130552103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Les données sociolinguistiques au prisme de l’analyse spatiale

International audienc

Les données sociolinguistiques au prisme de l’analyse spatiale

International audienc

Les données sociolinguistiques au prisme de l’analyse spatiale

International audienc