Mining Relation Reversals in the Evolution of SNOMED CT Using MapReduce
Shiqiang Tao MS Licong Cui PhD, Wei Zhu Mengmeng Sun
We present a scalable approach, using cloud computing, to systematically extract all hierarchical relation reversals among 8 SNOMED CT versions from 2009 to 2014. Taking advantage of our MapReduce algorithms for computing transitive closure and large-scale set operations, 48 reversals were found through 28 pairwise comparison of the 8 versions in 18 minutes using a 30-node local cloud, to completely cover all possible scenarios.
Mining Relation Reversals Using MapReduce
