Title: Mining novel connections from online biomedical text databases using semantic query expansion and semantic-relationship pruning

Authors: Xiaohua Hu, Xuheng Xu

Addresses: College of Information Science and Technology, Drexel University, Philadelphia, PA 19036, USA. ' College of Information Science and Technology, Drexel University, Philadelphia, PA 19036, USA

Abstract: This paper proposes a semantic-based approach for mining novel connections from biomedical literature. The method takes advantage of the biomedical ontologies, MeSH and UMLS, as the source of semantic knowledge. A prototype system, Biomedical Semantic-based Knowledge Discovery System (Bio-SbKDS), is designed to uncover novel hypotheses/connections hidden in biomedical literature through semantic query expansion and semantic-relationship pruning. Bio-SbKDS can automatically generate relevant search terms to retrieve the semantic-relevant articles from the online biomedical text databases. Using the semantic types and semantic relations of the biomedical concepts, Bio-SbKDS can identify the relevant concepts collected from Medline and generate the novel hypothesis between these concepts. Bio-SbKDS successfully replicates Dr. Swanson|s two famous discoveries: Raynaud disease/fish oil and migraine/magnesium. Compared with previous approaches, our methods search much less articles, generate much less but more relevant novel hypotheses and require much less human intervention in the discovery procedure.

Keywords: information extraction; text mining; query generation; information retrieval; biomedical databases; online databases; full text databases; semantic query expansion; semantic-relationship pruning; biomedical literature; biomedical ontologies; information retrieval; search terms; semantic network.

DOI: 10.1504/IJWGS.2005.008321

International Journal of Web and Grid Services, 2005 Vol.1 No.2, pp.222 - 239

Published online: 02 Dec 2005 *

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