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Mining Novel Knowledge from Biomedical Literature using Statistical Measures and Domain Knowledge
2016
Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '16
The problem of inferring novel knowledge from implicit facts by logically connecting independent fragments of literature is known as Literature Based Discovery(LBD). In LBD, to discover hidden links, it is important to determine the relevancy between concepts using appropriate information measures. In this study, to discover interesting and inherent links latent in large corpora, nine distinct methods, comprising variants of statistical information measures and derived semantic knowledge from
doi:10.1145/2975167.2975200
dblp:conf/bcb/JhaJ16
fatcat:ldtlfdods5hn7n4hxonqbc7fsq