title: Using a search engine-based mutually reinforcing approach to assess the semantic relatedness of biomedical terms.
abstract: BACKGROUND
  Determining the semantic relatedness of two biomedical terms is an important task for many text-mining applications in the biomedical field. Previous studies, such as those using ontology-based and corpus-based approaches, measured semantic relatedness by using information from the structure of biomedical literature, but these methods are limited by the small size of training resources. To increase the size of training datasets, the outputs of search engines have been used extensively to analyze the lexical patterns of biomedical terms.
  
  
  RESULTS
  In this work, we propose the Mutually Reinforcing Lexical Pattern Ranking (ReLPR) algorithm for learning and exploring the lexical patterns of synonym pairs in biomedical text. ReLPR employs lexical patterns and their pattern containers to assess the semantic relatedness of biomedical terms. By combining sentence structures and the linking activities between containers and lexical patterns, our algorithm can explore the correlation between two biomedical terms.
  
  
  CONCLUSIONS
  The average correlation coefficient of the ReLPR algorithm was 0.82 for various datasets. The results of the ReLPR algorithm were significantly superior to those of previous methods.
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, Republic of China.
authors.forename: Yi-Yu
authors.initials: YY
authors.lastname: Hsu
authors.affiliation: Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan, Republic of China.
authors.forename: Hung-Yu
authors.initials: HY
authors.lastname: Chen
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, Republic of China ; Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan, Republic of China.
authors.forename: Hung-Yu
authors.initials: HY
authors.lastname: Kao
mesh_terms: D000465:Algorithms; D035843:Biomedical Research; D019295:Computational Biology; D010363:Pattern Recognition, Automated; D057386:Search Engine / Q000592:standards*; D012660:Semantics