TY  - JOUR
T1  - Aggregating Automatically Extracted Regulatory Pathway Relations
JF  - IEEE Transactions on Information Technology in Biomedicine
Y1  - 2006
A1  - Marshall,Byron
A1  - Su,Hua
A1  - McDonald,Daniel
A1  - Eggers,Shauna
A1  - Chen,Hsinchun
KW  - Accounting
KW  - BIS
AB  - 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. Organizational 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.
VL  - 10
UR  - http://people.oregonstate.edu/~marshaby/Papers/Marshall_IEEE_TITB_2005.pdf
CP  - 1
U2  - a
U4  - 648208384
ID  - 648208384
ER  -