Aggregating automatically extracted regulatory pathway relations

作者：Marshall B^*; Su H; McDonald D; Eggers S; Chen H

来源：IEEE Transactions on Information Technology in Biomedicine, 2006, 10(1): 100-108.

DOI：10.1109/TITB.2005.856857

• knowledge representation
• regulatory pathway analysis
• relation parsing

Automatic tools to extract information from biomedical texts are needed to help researchers leverage the vast and increasing body of biomedical literature. While several biomedical relation extraction systems have been created and tested, little work has been done to meaningfully organize the extracted relations. Organizatnonal processes should consolidate multiple references to the same objects over various levels of granularity, connect those references to other resources, and capture contextual information. We propose a feature decomposition approach to relation aggregation to support a five-level aggregation framework. Our BioAggregate tagger uses this approach to identify key features in extracted relation name strings. We show encouraging feature assignment accuracy and report substantial consolidation in a network of extracted relations.

• 出版日期2006-1