OpenDMAP System
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An OpenDMAP is a Biomedical Entity Mention Normalization System.
- http://bionlp.sourceforge.net/
- OpenDMAP: an ontology-driven, rule-based concept analysis and information extraction system
- http://opendmap.sourceforge.net/
- OpenDMAP is an ontology-driven, rule-based concept analysis and information extraction system. Unlike traditional parsers, OpenDMAP does not have a lexicon that maps from words to all the possible meanings of these words. Rather, each concept is associated with phrasal patterns that are used to recognize that concept. OpenDMAP processes texts to recognize concepts and relationships from a knowledge-base. OpenDMAP uses Protégé knowledge-bases to provide an object model for the possible concepts that might be found in a text. Protégé models concepts as classes that participate in abstraction and packaging hierarchies, and models relationships as class-specific slots.
- (BaumgartnerLJCPLWMCH, 2008) ⇒ William A. Baumgartner Jr, Zhiyong Lu, Helen L Johnson, J Gregory Caporaso, Jesse Paquette, Anna Lindemann, Elizabeth K White, Olga Medvedeva, K Bretonnel Cohen, and Lawrence Hunter. (2008). “Concept recognition for extracting protein interaction relations from biomedical text.
- A key focus in our work, and for the protein-protein interaction extraction task (interaction pair subtask [IPS]) in particular, was the use of a concept recognition system being developed by our group. Called Open source Direct Memory Access Parser (OpenDMAP), it is a modern implementation of the DMAP paradigm first developed by Riesbeck [9], Martin [10], and Fitzgerald [11]. The earliest descriptions of the paradigm assumed that a DMAP system would approach all levels of linguistic analysis through a single optimization procedure. In this work we show that analysis can be modularized, and even externalized, without losing the essential semantic flavor of the DMAP paradigm. Hunter and coworkers [3] have described OpenDMAP in detail.