RCLN : Knowledge Representation and Natural Language
The RCLN team is interested in language for its expressive power, and in knowledge representation, particularly as a tool for natural language processing.
This work includes both fundamental and applied research with an original combination of skills in automatic language processing, linguistics, textual data mining, semantic information retrieval, heterogeneous knowledge acquisition and management.
The team’s project aims to articulate language and knowledge to improve the processes of knowledge acquisition and textual analysis and the exploitation and exploration of corpora.
RCLN’s research is organised into three main themes :
- syntactic and semantic analysis semantic
- annotation and textual exploration
- acquisition of knowledge from texts
With a transversal axis articulating these different themes and showing that the analysis of texts calls upon data and knowledge while contributing to their acquisition with the aim of creating a virtuous circle between language, data and knowledge.
The team plans to work on various scientific literature mining projects and to test the methods developed on different types of corpus and fields (digital humanities, computer science, etc.).