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The research activities carried out by the ADVANSE team are in the field of the analysis of large databases in order to extract new knowledge. They relate to the following three areas:

  • Data mining (DM) which continues historical work with particular emphasis on the proposal of pattern mining approaches integrating either new dimensions such as, for example, the spatial dimension in the case of spatio-temporal patterns and trajectories or else the dimensions associated with the different types of arcs which may exist in multigraphs;
  • Analytical Visualization (VA) which emphasizes analytical reasoning facilitated by interactive visual interfaces. Such interfaces, integrating various methods of information representation, interaction or even automatic knowledge extraction, aim to allow users to extract, from complex and / or heterogeneous data, information directly supporting analysis, planning and decision making;
  • Machine learning (ML) which, in addition to the various works carried out on the definition of new machine learning approaches (eg detection of rare clusters, labeling of topics), focuses on taking into account small or very large data sets via traditional approaches (eg SVM, Gradient Boosting, active learning) or more recent (eg deep learning). Indeed, Deep Learning has shown its effectiveness for classifying data in large volumes or with large numbers of dimensions (e.g. images, sounds, texts). However, the explicability of the results, or even the definition of a good architecture remain very experimental exercises and constitute real challenges for the scientific community.

The ADVANSE team, in its three axes, is developing work on both theoretical and experimental bases to address the associated issues. The team is taken to cross these different axes for various projects.

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Learning Automatic Term Extraction Réalité Virtuelle Neural networks Ontology Training Données textuelles Evaluation Citizen science Social media Angular Base de données intégrée Réseaux sociaux Managers Graph neural networks TAL Presence-only data Aménagement du territoire Semantic annotation Species distribution model Species identification Commerciaux Prediction Web Mining Remote sensing Machine Learning Top-k LifeCLEF Graph Mining Bird identification Visual analytics Natural Language Processing Methods comparison Artificial intelligence Apprentissage supervisé Text mining Machine learning Opinion mining Médecine Data mining Benchmark Species distribution models Sequential patterns Données multi-sources SMS Corpus Signal processing Visualisation d'information Hydro-ecology Clustering Text categorization ALGORITHME Deep learning Fouille de données Classification Social networks Emotion analysis Cancer du sein Virtual Reality Data Mining Environmental data NLP Model performance Visualisation Diversity Suicide Fouille de textes Analyse de sentiments Multilayer graphs Compétences sociales Categorical data Médias sociaux Méta-descripteurs Fouille de texte Controversy detection Intelligence artificielle Apprentissage Analyse d’opinions Graphs Biomedical ontologies Information extraction Predictive power BioNLP Visualization Nlp Polarity detection Aggregation Text Mining Sentiment analysis Satellite image time series ANALYSE DE DONNEES Recommendation Algorithms Plant identification Species prediction Information visualization Natural language processing Species distribution Biodiversity Animal epidemiology