Termidentifiering
Termidentifiering is the automatic process of identifying and extracting domain-specific terms from text. The goal is to produce a usable terminology or glossary that can support indexing, search, knowledge representation, and linguistic analysis. Terms may be single words or multiword expressions, such as neural network or clinical trial protocol.
The task combines linguistic analysis with statistical signals. Preprocessing includes tokenization, sentence splitting, and part-of-speech tagging;
Common approaches are rule-based methods that rely on morpho-syntactic patterns, statistical methods that use frequency-based measures
Evaluation typically uses precision, recall, and F1 against a gold-standard term list or glossary. Performance depends
Applications include building domain terminologies for ontologies and knowledge graphs, improving information retrieval and indexing, supporting
Key challenges include identifying boundaries of multiword terms, handling polysemy and homonymy, domain drift, cross-domain variability,