Symbolic reasoning

One of the two main branches of Artificial Intelligence (AI) resides in symbolic knowledge-driven approaches. Symbolic AI systems represent language phenomena via logical rules.

Lexical analysis: electronic lexicons, formalized rules

Lexical analysis is the first step for Natural Language Processing tasks. Words or combinations of words (compound words) occur in texts in their inflected forms (conjugated verbs, plurals, etc.) or in the form of variants such as abbreviations. Lexico-semantic resources such as formalized electronic dictionaries of simple and compound biomedical terms constitute a valuable resource.

• Morphological analysis
• Syntactic and semantic analysis

Patterns matching: Local grammars, finite state automata

Local grammars and finite state automata are developed to describe specific rules of the French medical language (syntactic constraints, lexical ambiguities) and locate occurrences of the patterns in texts. Information and relation extraction tasks are performed based on pattern matching.

• Information Extraction (IE)
• Named Entity Recognition (NER)
• Relation Extraction (RE)

Knowledge graphs

Representation of information and logical relations via rules, knowledge graphs, ontologies, semantic nets so that a computer system can solve complex tasks. 

• Semantic representation of concepts & relationships