Semantic based real-time clustering for PubMed literatures

Authors:
Ruey-Ling Yeh;Ching Liu;Ben-Chang Shia;I-Jen Chiang;Wen-Wen Yang;Hsiang-Chun Tsai
Affiliations:
Division of Biometrics, Graduate Institute of Agronomy, National Taiwan University, Taipei, Taiwan;Division of Biometrics, Graduate Institute of Agronomy, National Taiwan University, Taipei, Taiwan;Department of Statistics and Information Science, Fu Jen Catholic University, Taipei, Taiwan;Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan and Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Medical Sciences, Taipei Medical University, Taipei, Taiwan;Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
Venue:
DS'07 Proceedings of the 10th international conference on Discovery science
Year:
2007

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Abstract

This paper addresses to use the latent semantic topology to real-time cluster the literatures retrieved by PubMed in response to clinical queries and evaluates its performance by professional experts. The result shows that semantic clusters properly offer an exploratory view on the returned search results, which saves users' time to understand them. Besides, most experts conceive that the documents assigned to the identical cluster are similar and the concepts of clusters are appropriate.