Patent ID: 11893503
Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A machine learning based semantic structural hole identification apparatus comprising:
at least one hardware processor;
an embeddings generator, executed by the at least one hardware processor, to map text elements of a corpus into an embedding space that includes a plurality of embeddings that are represented as vectors;
a semantic network generator, executed by the at least one hardware processor, to generate, based on semantic relatedness between each pair of the vectors of the embedding space, a semantic network;
a semantic space hole identifier, executed by the at least one hardware processor, to identify semantic holes in the semantic network;
a data porosity analyzer, executed by the at least one hardware processor, to determine, based on a number of the semantic holes in comparison to the text elements of the corpus, semantic porosity of the corpus;
a void filler, executed by the at least one hardware processor, to fill the semantic holes;
a porosity impact analyzer, executed by the at least one hardware processor, to determine, based on the semantic porosity of the corpus, a performance impact of utilization of the corpus to generate an application by using the text elements of the corpus without filling the semantic holes; and
an application generator, executed by the at least one hardware processor, to
determine whether the performance impact of utilization of the corpus to generate the application without filling the semantic holes is greater than or equal to an impact threshold; and
based on a determination that the performance impact of utilization of the corpus to generate the application without filling the semantic holes is greater than or equal to the impact threshold, utilize the text elements of the corpus with the semantic holes filled by the void filler to generate the application.