Dependency-Based Relation Mining for Biomedical Literature

We describe techniques for the automatic detection of relationships among domain entities (e.g. genes, proteins, diseases) mentioned in the biomedical literature. Our approach is based on the adaptive selection of candidate interactions sentences, which are then parsed using our own dependency parser. Specific syntax-based filters are used to limit the number of possible candidate interacting pairs. oach has been implemented as a demonstrator over a corpus of 2000 richly annotated MedLine abstracts, and later tested by participation to a text mining competition. In both cases, the results obtained have proved the adequacy of the proposed approach to the task of interaction detection.

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Fabio Rinaldi, Gerold Schneider, Kaarel Kaljurand, Michael Hess
• Keywords: Candidate Interacting Pairs, Candidate Interactions Sentences, Education, LREC 2008, Specific Syntax-based Filters