Title: Development and evaluation of a triple parser to enable visual searching with a biomedical search engine
Authors: Myungjae Kwak; Gondy Leroy; Mikyung Kim
Addresses: School of Information Technology, Middle Georgia State College, Macon, GA 31206, USA ' School of Information Systems and Technology, Claremont Graduate University, Claremont, CA 91711, USA ' Division of Gynecologic Oncology, Irvine Medical Center, University of California, Orange, CA 92868, USA
Abstract: We describe a new biomedical search engine that enables visual searching and utilises predicates instead of phrases. We report on the development and evaluation of the triple parser, the most essential component of the search engine, which extracts the necessary predicates from the biomedical text. Using texts from three biomedical related sites (N = 180), we compared the parser's output with a gold standard independently created by a medical expert. The parser achieved more than 91% precision and recall. Its individual components showed different strengths with Finite State Automata being excellent for achieving high recall, while Support Vector Machines improved the precision.
Keywords: search engines; triple parser; text mining; finite state automata; kernel methods; support vector machines; SVM; biomedical search; visual searching; biomedical texts; information retrieval.
International Journal of Biomedical Engineering and Technology, 2012 Vol.10 No.4, pp.351 - 367
Available online: 01 Mar 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article