Foundations of knowledge extraction and management


-       Supervised learning: kernel machines, vector machines, formal neural networks, probabilistic models, rule learning, ensemble methods, regression…

-       Clustering: conceptual clustering, partitioning methods, neural methods, hierarchical methods, multiview, multistrategy, incremental, or collaborative clustering

-       Model selection

-       Pattern mining: itemsets, sequences, trees, graphs...

-       Outlier and anomaly detection

-       Recommendation systems

-       Other paradigms: semi-supervised, active or multistrategy machine learning


-       Statistical methods in data mining

-       Symbolic learning, inductive logic programming

-       Topological learning, mathematical varieties

-       Visual data mining

-       Data mining and constraints

-       Incremental data mining

-       Scalable data mining algorithms

-       Distributed/parallel systems for data mining

-       Symbolic data analysis


-       Structured, semi-structured, textual data…

-       Semantically heterogeneous data / multimedia, spatial, images, video, audio… data / data populating knowledge models, relational data, network data, graph data

-       Geolocated, temporal, spatial data

-       Data annotated with ontologies, exploited within the semantic Web

-       Voluminous, complex, dynamic data…

-       Open data

-       Social data

Methodologies for knowledge extraction and management

-       Data acquisition, collection, preprocessing, filtering, data reduction, selection and feature modification

-       Data quality and knowledge criteria and evaluation

-       Data integration (ETL, data warehouses, mediation…)

-       Knowledge integration in the extraction process

-       Knowledge and ontology management (acquisition, storage, update, interoperability, interconnection, evolution)

-       Analytical visualization, OLAP, person-machine interaction in data mining

-       Information and data traceability, security and integrity

-       Platforms and systems for KDD

-       Comparative studies by benchmarking

-       Evaluation protocols and model validation from user samples

-       Experimental studies on voluminous data

Knowledge extraction and management in emerging domains

-       Social: relationship analysis, on-line communities, social networks…

-       Mobility, geolocation, ambient, ubiquitous

-       Behavior modeling

-       Electronic commerce, online advertisement

-       Opinion, news, microblogging mining

-       Open data

-       Linked Data

-       Crowdsourcing

Applications of knowledge extraction and management

-       Enterprise memory, technological watch

-       Intrusion detection, fraud prevention

-       Epidemics modeling, clinical research, health monitoring

-       Customer relationship, network and system management

-       Sustainable development, intelligent transport

-       Other applications in domains such as medicine, biology, chemistry, finance, insurance…