Relevance Ranking Algorithm for Linking Literatures and Proprietary Experimental Biomedical Data
Date Issued
2015
Date
2015
Author(s)
Chen, Hsi
Abstract
In the biomedical research works, mapping researchers’ proprietary experiment data to public research literatures is an important work. This study presents a relevance ranking algorithm, calculate the relevance score for literature abstracts and locus names, and sort the results. Afterward, locus names are linked to the researchers’ proprietary experiment databases and using web techniques automatically plot the charts for the relevant proprietary data; through these processes, the researchers can efficiently get the relevance between their proprietary data and the public papers also can help them to find more available research works.
Subjects
Relevance ranking
Bioinformatics
Literature search
Type
thesis
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ntu-104-R02525067-1.pdf
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