Title :
A Hybrid Approach for Biomedical Entity Name Recognition
Author :
Gong, Le-Jun ; Yuan, Yi ; Wei, You-Bing ; Sun, Xiao
Author_Institution :
Dept. of Biol. Sci. & Med. Eng., Southeast Univ., Nanjing, China
Abstract :
Biomedical named entity recognition, an important step, makes preparation for extracting information from biomedical textual resources. This paper presents a hybrid approach to recognize biomedical entity, which includes POS (Part-of-Speech) tagging, rules-based and dictionary-based approach using biomedical ontology. Experiment results show our approach can find untagged biomedical entity name in the GENIA 3.02 corpus for aiding biologist tagging biomedical entity in the biomedical literature and obtain a recall of 66%, a precision of 78% and an F-score 71.5% for the test dataset extracted from the GENIA 3.02 corpus.
Keywords :
biology computing; data mining; diseases; genetics; medical information systems; molecular biophysics; ontologies (artificial intelligence); GENIA 3.02 corpus; biomedical entity name recognition; biomedical literature; biomedical ontology; dictionary-based approach; disease; gene; hybrid approach; part-of-speech tagging; rules-based approach; text mining; Biomedical engineering; Data mining; Dictionaries; Diseases; Engineering in medicine and biology; Laboratories; Ontologies; Proteins; Tagging; Text mining;
Conference_Titel :
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4132-7
Electronic_ISBN :
978-1-4244-4134-1
DOI :
10.1109/BMEI.2009.5302480