Dynamic generation of concepts hierarchies for knowledge discovering in bio-medical linked data sets

Since most bio-medical Linked Data Sets are simply extracted from the Relational database, lots of them are lack of ontology or concept hierarchy structure for user better understanding the data sets. This problem also limited usage of bio-medical Linked Data Sets. To resolve the problem, this paper introduced a method to dynamically generate the concept hierarchy from the Linked Data Sets. Based on the hierarchical clustering algorithm, we applied Vector Space Model(VSM) and Jaccard's Coefficient(JC) to formalize the hierarchy structure after pre-processing data. We implemented our method using two Linked Data Sets: DrugBank and Diseasome from Linked Life Data and evaluated performance with the gold standard.

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