Upcoming Talks
Title: EMBEDD-ER : EMBEDDing Educational Resources Using Linked Open Data
Speaker: Aymen Bazouzi
Place and Time: Rennes – Room TBD & Teams via the DRUID Channel – 28 March at 1:00 PM
Description:
There are a lot of educational resources publicly available online. Recommender systems and information retrieval engines can help learners and educators navigate in these resources. However, the available educational resources differ in format, size, type, topics, etc. These differences complicate their use and manipulation which raised the need for having a common representation for educational resources and texts in general. Efforts have been made by the research community to create various techniques to homogeneously represent these resources. Although these representations have achieved incredible results in many tasks, they seem to be dependent on the writing style and not only on the content. Furthermore, they do not generate representations that reflect a semantic representation of the content. In this work, we present a new task-agnostic method (EMBEDD-ER) to generate representations for educational resources based on document annotation and Linked Open Data (LOD). It creates representations that are focused on the content, compact, and can be generalized to unseen resources without requiring extra training. The resulting representations encapsulate the information found in the resources and project similar resources closer to one another than to non-similar ones. Empirical tests have shown promising results both visually and in a subject classification task.
Former Talks
Title: Analysis and prediction of the commercial speed in a public urban transport network
Speaker: Erwan Vincent
Place and Time: Rennes – Room TBD & Teams via the DRUID Channel – 21 March at 1:00 PM
Description:
In the metropolis of Rennes as in other cities, buses evolve in a complex environment that is the urban environment. This environment contains many “factors” that can positively or negatively influence the speed of buses. In a paper to be submitted in the following months, I have proposed an analysis of the different factors that can impact buses speed and the use of these different factors in a machine learning model. This is to desmonstrate that the knowledge of the environment where buses evolve allow to know with a certain degree of accuracy their future performance in this same environment.
Title: Article archive explorer
Speaker: Cédriane Prohin
Place and Time: Rennes – Room TBD & Teams via the DRUID Channel – 14 March at 1:00 PM
Description:
Presentation of website that allows to collect archive articles of “LA NATURE” using keyword exploration.
Title: Contribution to automated license analysis – state of the art
Speaker: Malo Revel
Place and Time: Rennes – Room Aurigny D165 & Teams via the DRUID Channel – 7 February at 1:00 PM
Title: Designing a temporal graph management system for IoT application domains.
Speaker: Maria Massri
Place and Time: Rennes – Aurigny (D165) – Tuesday, the 6th of December at 1:00 PM – 6 December 2022 at 1:00 PM
Title: Numérique responsable ? Moins vite, moins haut, moins fort !
Speaker: Olivier Ridoux
Place and Time: Rennes – Aurigny (D165) & Teams via the DRUID Channel – 8 November 2022
Description:
Si on considère qu’une posture responsable consiste à ne pas se fermer aux angles morts une fois qu’ils nous sont révélés, on voit que le numérique responsable (et pareillement le tourisme responsable, l’agriculture responsable, etc.) doit accepter des contraintes qui ne viennent pas des spécialistes du domaines, et qui sont exprimées en des termes inhabituels pour les spécialistes, comme des joules, des tonnes de GES ou des m3 d’eau. Être responsable signifie seulement respecter ces contraintes. À l’heure actuelle, ces contraintes ne sont pas encore formulées explicitement, et il revient alors au numérique responsable de ne pas attendre qu’elles le soient mais plutôt de les anticiper. Les contraintes à anticiper sont tellement fortes qu’on doit s’attendre à devoir faire moins vite, moins haut et moins fort, même si il n’est pas exclu que le temps passant l’état de l’art progresse et permette d’aller plus vite, plus haut et plus fort, mais toujours en respectant les contraintes.
Title: Imperfect Labels with Belief Functions for Active Learning
Speaker: Arthur Hoarau
Place and Time: Rennes – Oléron (A008) & Teams via the DRUID Channel – 17 October 2022
Abstract:
This paper offers a way to deal with uncertain and imprecise labeled data using Dempster-Shafer theory and active learning. An evidential version of K-NN that classifies a new example by observing its neighbors was earlier introduced.
We propose to couple this approach with active learning, where the model uses only a fraction of the labeled data, and to compare it with non-evidential models.
A new computable parameter for EK-NN is introduced, allowing the model to be both compatible with imperfectly labeled data and equivalent to its first version in the case of perfectly labeled data.
This method increases the complexity but provides a way to work with imperfectly labeled data with efficient results and reduced labeling costs when coupled with active learning. We have conducted tests on real data imperfectly labeled during crowdsourcing campaigns.
Title: State of the Art of Aymen Bazouzi’s PhD entitled : “Combining Educational Resources Through Graph Representation Learning”
Speaker: Aymen Bazouzi
Place and Time: Rennes – Aurigny (D165) & Inria Cisco – 07 June 2022
Title: State of the Art of Erwan Vincent’s PhD entitled : “Automatic learning and simulation for the identification and prediction of the determining factors of the quality of service of high service level buses”
Speaker: Erwan Vincent
Place and Time: Rennes – Aurigny (D165) & Teams via the DRUID Channel – 24 Mai 2022
Title: Clock-G: A temporal graph management system with a space-efficient storage technique
Speaker: Maria Masri
Place and Time: Rennes – Oléron (A008) & Teams via the DRUID Channel – 6 Mai 2022
Abstract:
In this paper, we discuss the design of a temporal graph management system Clock-G and introduce a new space-efficient storage technique δ-Copy+Log. Clock-G is designed by the developers of the Thing’in platform and is currently being deployed into production. It differentiates from existing temporal graph management systems by adopting the δ-Copy+Log technique. This technique targets the mitigation of the apparent trade-off between the conflicting goals of the reduction of space usage and acceleration of query execution time. Our experimental results demonstrate that the δ-Copy+Log presents an overall better performance as compared to traditional storage methods in terms of space usage and query evaluation time.
Title: Presentation of PhD work
Speaker: Mathieu Chambe
Place and Time: Rennes-Aurigny (D165) & Teams via the DRUID Channel – 9 November 2021
Title: PhD defense rehearsal
Speaker: Gauthier Lyan
Place and Time: Rennes-Aurigny (D165) – 21 September 2021
Title: Development of Croudsourcing campaigns
Speaker: Thomas Hamon
Place and Time: Teams – 22 June 2021
Title: CSID rehearsal
Speaker: François Mentec
Place and Time: TEAMS – 8 June 2021
Title: CSID rehearsal
Speaker: Maria Massri
Place and Time: ZOOM – 1 June 2021
Title: CSID rehearsal
Speaker: Constance Thierry
Place and Time: TEAMS – 11 May 2021
Title: Data-centric Workflows for Croudsourcing Applications (PhD defense rehearsal)
Speaker: Rituraj Singh
Place and Time: ZOOM – 27 April 2021
Title: Belief Shift Clustering
Speaker: Zuowei Zhang
Place and Time: TEAMS – 26 January 2021
Abstract:
It is still a very challenging task to characterize the uncertainty and imprecision between singleton (specific) clusters with arbitrary shapes and sizes in the space. To derive such a problem, this paper introduces a new method, called belief shift clustering (BSC), for object data via extending mean shift or mode seeking under the framework of belief functions, which mainly contains two characteristics. First, the query object is preliminarily assigned as the noise, precise, or imprecise one based on the notion of “belief shift”. Second, partial credal redistribution with dynamic cluster centers, inspired by fuzzy/possibilistic and evidential partition, to avoid the “uniform effect”, is established to reassign the imprecise object to the specific cluster or related meta-cluster. Once assigned to meta-cluster, it indicates that the specific clusters involved in the meta-cluster cannot be distinguished for the object since it may lie in the overlapping or intermediate areas of different specific clusters. By doing this, the BSC can reasonably characterize the uncertainty and imprecision between specific clusters, regardless of their shapes and sizes in the space. The effectiveness of the proposed method has been validated on several synthetic and real data sets by critically comparing with that of other related methods.
Title: Web Bias Monitoring
Speaker: Théo JAMMES-BEUVE, Thomas LE FLOCH and Olivier MEYER
Place and Time: Rennes – Lipari (F202) and 30 June 2020
Title: The Thing’in platform
Speaker: Maria Massri
Place and Time: Rennes -Aurigny(D165) and 13 March 2020
Abstract:
Title: Public transportation
Speaker: Gauthier Lyan
Place and Time: Rennes -Aurigny(D165) and 03 March 2020
Abstract:
“Nowadays, climate change has become an actual issue to address for both scientists and politicians. If the former can prove to the later that there actually are solutions to reduce the impact of human activities on the climate, the later cannot easily act without appropriate tools that facilitate choices on what to act on.
Public transportation systems are wide and complex, involving many stakeholders and heterogeneous factors that have an impact on their efficiency, hence global impact. We will propose a software approach that offer the possibility to study public transportation systems both in temporal and spatial dimensions, offering predictions of commercial speed in known and unknown environment, based on historical data and available exogenous data. The purpose of this research is to enable decision-makers to make better decisions about public transportation.”
We will discuss the data sources we already/should have, and if our assumptions about them make sense or not.
We will discuss the framework we are being imagining.
Title: Privacy and ethical issues of AI in legal systems
Speaker: Louis Béziaud
Place and Time: Rennes -Aurigny(D165) and 18 February 2020
Title: From databases to artificial intelligence
Speaker: Zoltan Miklos
Place and Time: Rennes -Aurigny(D165) and 11 February 2020
Abstract:
Repetition for the HDR presentation.
Title: Modeling uncertainty and inaccuracy on data from crowdsourcing platforms: MONITOR
Speaker: Constance Thierry
Place and Time: Rennes -Aurigny(D165) and 21 January 2020 (visio from Lannion)
Abstract:
Repetition for the EGC2020 presentation.
Title: Building metro map of scientific topics using hierarchy alignments
Speaker: Ian Jeantet
Place and Time: Rennes -Aurigny(D165) and 14 January 2020
Abstract:
Presentation of the my joint work done with the Griffith University during my mobility in Australia. I’ll explain how we ended up to build metro maps of scientific topics to study the evolution of science through time.
Title: Feedback from the Shonan Meeting on Crowdsourcing/Future of Work
Speaker: David Gross-Amblard
Place and Time: Rennes -Aurigny(D165) and 17 December 2019
Title: Crowdsourcing the database course with HEADWORK
Speaker: Adrien Wacquet (2019 Summer Internship)
Place and Time: Rennes -Aurigny(D165) and 03 December 2019
Title: Web crawler & and the DIFFIX attack
Speaker: Antonin Voyez
Place and Time: Rennes -Aurigny(D165) and 19 November 2019
Abstract:
Presentation of a web crawler made for the PROFILE project and a short presentation of the current work done for my upcoming thesis with ENEDIS : linear reconstruction applied to the DIFFIX system.
Title: The anonymization of personal data: myth, limits, and successes
Speaker: Tristan Allard, Joris Duguépéroux, Tompoariniaina Andriamilanto
Place and Time: Rennes -Oleron(A008) and 12 March 2019
Link: Privacy Games @ Festival des Libertés Numériques
Title: Overlapping hierarchical clustering
Speaker: Ian Jeantet
Place and Time: Rennes -Oleron(A008) and 12 February 2019
Abstract:
Agglomerative clustering methods have been widely used by many research communities to explore hierarchical structures in their data. The produced cluster hierarchies contribute to understanding the hierarchical structures that are present in complex data. However the agglomerative methods necessarily result in a tree structure, where one has to make a split decision too early in the construction process, that can affect the conclusions one can make about the obtained hierarchical structure. In various settings, one needs a richer hierarchical structure to describe the clusters of the data. Moreover, clusters might also overlap. In this paper, We propose a framework that enables to compute hierarchical structures represented as directed acyclic graphs rather than trees. Our bottom-up method creates clusters with density-based merging criteria, such that the various clusters can overlap.
Title: Integrating uncertain data using user feedback in crowdsourcing applications
Speaker: Marion Tommasi
Place and Time: Rennes -Oleron(A008) and 22 January 2019
Abstract:
Crowdsourcing applications are used in many domains to perform tasks which are difficult for computers or to gather knowledge using a crowd of people. To execute a task in a crowdsourcing application, human workers by performing some micro-tasks and the resulting data is integrated into the system to proceed with the completion of the global task. However, the data provided by workers is uncertain as human workers can make mistakes or eventually intentionally give a wrong result. We want to use the feedback of other workers to evaluate the trust in the data at any time of the workflow. Ultimately, we want to use this trust to have a workflow which adapts itself depending on the data ant the perceived trust in it to improve data quality. I will first present a model for crowdsourcing applications then present the model for user feedback.
Title: Data-Centric workflow for Complex Crowdsourcing Applications
Speaker: Rituraj Singh
Place and Time: Rennes -Oleron(A008) and 15 January 2019
Abstract:
Crowdsourcing has emerged as a major paradigm for accomplishing work by paying a small sum of money and alluring the worker whole across the globe. However, the targeted tasks at crowdsourcing platforms are relatively simple, uncomplicated and are independent. In this work, we propose a novel data-centric workflow model for the design of complex crowdsourcing tasks with dependencies. The model allows orchestration of simple tasks, handles data and crowd workers, allows concurrency, and in addition provides high-level constructs allowing decomposition of complex tasks into orchestrations of simpler subtasks. We first define the syntax and semantics of the model, and then consider its formal properties, starting with the question of termination of a complex workflow (i.e., whether a system has non-terminating runs). Unsurprisingly termination is undecidable even for the simplest models. However, upon restrictions that are sensible in the context of crowdsourcing (namely that a crowd worker only has a bounded number of contributions in a workflow ), termination becomes decidable. We then extend the termination question to address the correctness of a workflow, i.e. the question of whether a terminating workflow always satisfies a constraint depicted in terms of the relation between the input of the workflow and its output.
