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Title: Assessment of approximate string matching in a biomedical text retrieval problem
Authors: Wang, J.F.
Li, Z.R. 
Cai, C.Z. 
Chen, Y.Z. 
Keywords: Bioinformatics
Data mining
Dynamic programming
Herbal medicine
Literature search
Medicinal plant
Smith-Waterman algorithm
Text matching
Word matching
Issue Date: Oct-2005
Citation: Wang, J.F., Li, Z.R., Cai, C.Z., Chen, Y.Z. (2005-10). Assessment of approximate string matching in a biomedical text retrieval problem. Computers in Biology and Medicine 35 (8) : 717-724. ScholarBank@NUS Repository.
Abstract: Text-based search is widely used for biomedical data mining and knowledge discovery. Character errors in literatures affect the accuracy of data mining. Methods for solving this problem are being explored. This work tests the usefulness of the Smith-Waterman algorithm with affine gap penalty as a method for biomedical literature retrieval. Names of medicinal herbs collected from herbal medicine literatures are matched with those from medicinal chemistry literatures by using this algorithm at different string identity levels (80-100%). The optimum performance is at string identity of 88%, at which the recall and precision are 96.9% and 97.3%, respectively. Our study suggests that the Smith-Waterman algorithm is useful for improving the success rate of biomedical text retrieval. © 2004 Elsevier Ltd. All rights reserved.
Source Title: Computers in Biology and Medicine
ISSN: 00104825
DOI: 10.1016/j.compbiomed.2004.06.002
Appears in Collections:Staff Publications

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