  The feature matching is a basic step in matching different datasets. This
article proposes shows a new hybrid model of a pretrained Natural Language
Processing (NLP) based model called BERT used in parallel with a statistical
model based on Jaccard similarity to measure the similarity between list of
features from two different datasets. This reduces the time required to search
for correlations or manually match each feature from one dataset to another.
