By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Data detailed on Bioinformatics have been presented. According to news reporting originating in Liaoning, People's Republic of China, by VerticalNews journalists, research stated, "Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts)."
The news reporters obtained a quote from the research from China Medical University and Hospital, "SemRep is used to extract semantic predications from the citations returned by a PubMed search. Cliques were identified from frequently occurring predications with highly connected arguments filtered by degree centrality. Themes contained in the summary were identified with a hierarchical clustering algorithm based on common arguments shared among cliques. The validity of the clusters in the summaries produced was compared to the Silhouette-generated baseline for cohesion, separation and overall validity. The theme labels were also compared to a reference standard produced with major MeSH headings. For 11 topics in the testing data set, the overall validity of clusters from the system summary was 10% better than the baseline (43% versus 33%)."
According to the news reporters, the research concluded: "While compared to the reference standard from MeSH headings, the results for recall, precision and F-score were 0.64, 0.65, and 0."
For more information on this research see: Clustering cliques for graph-based summarization of the biomedical research literature. Bmc Bioinformatics, 2013;14():182. (BioMed Central - www.biomedcentral.com/; Bmc Bioinformatics - www.biomedcentral.com/bmcbioinformatics/)
Our news correspondents report that additional information may be obtained by contacting H. Zhang, Dept. of Medical Informatics, China Medical University, Shenyang, Liaoning 110001, People's Taiwan. Additional authors for this research include M. Fiszman, D. Shin, B. Wilkowski and T.C Rindflesch.
Keywords for this news article include: Asia, Liaoning, Bioinformatics, People's Republic of China.
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