Method, apparatus, and computer program product for improving network database functionalities

An apparatus for improving network database precision and recall, the apparatus comprising at least one processor and at least one non-transitory memory including program code, the at least one non-transitory memory and the program code configured to, with the at least one processor, cause the apparatus to at least:

• receive, from a client device, a network database search query associated with one or more network databases;
• in response to receiving the network database search query, query the one or more network databases to identify a plurality of datasets;
• determine a plurality of taxonomy attributes, each of the plurality of taxonomy attributes being associated with at least one dataset of the plurality of datasets;
• calculate a taxonomy entropy based on the plurality of taxonomy attributes;
• compare the taxonomy entropy to an entropy threshold;
• in response to the taxonomy entropy satisfying the entropy threshold, generate a dataset ranking based on relevance scores associated with the plurality of datasets;
• dynamically generate one or more taxonomy refinements based on the dataset ranking;
• calculate a refinement count for the one or more taxonomy refinements;
• determine whether the refinement count satisfies a refinement maximum threshold;
• and
• in response to determining that the refinement count satisfies the refinement maximum threshold:
• aggregate the plurality of taxonomy attributes at a parent taxonomy level;
• generate a taxonomy tree based at least in part on the one or more taxonomy refinements, wherein the taxonomy tree is configured to link the one or more taxonomy refinements to the plurality of datasets;
• and
• output, to the client device, the plurality of datasets and the taxonomy tree to improve the network database precision and recall.

A computer program product for improving network database precision and recall, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to:

• receive, from a client device, a network database search query associated with one or more network databases;
• in response to receiving the network database search query, query the one or more network databases to identify a plurality of datasets;
• determine a plurality of taxonomy attributes, each of the plurality of taxonomy attributes being associated with at least one dataset of the plurality of datasets;
• calculate a taxonomy entropy based on the plurality of taxonomy attributes;
• compare the taxonomy entropy to an entropy threshold;
• in response to the taxonomy entropy satisfying the entropy threshold, generate a dataset ranking based on relevance scores associated with the plurality of datasets;
• dynamically generate one or more taxonomy refinements based on the dataset ranking;
• calculate a refinement count for the one or more taxonomy refinements;
• determine whether the refinement count satisfies a refinement maximum threshold;
• and
• in response to determining that the refinement count satisfies the refinement maximum threshold:
• aggregate the plurality of taxonomy attributes at a parent taxonomy level;
• generate a taxonomy tree based at least in part on the one or more taxonomy refinements, wherein the taxonomy tree is configured to link the one or more taxonomy refinements to the plurality of datasets;
• and
• output, to the client device, the plurality of datasets and the taxonomy tree to improve the network database precision and recall.