Python package for performing Entity and Text Matching using Deep Learning
DeepMatcher is a Python package for performing entity and text matching using deep learning. It provides built-in neural networks and utilities that enable you to train and apply state-of-the-art deep learning models for entity matching in less than 10 lines of code. The models are also easily customizable – the modular design allows any subcomponent to be altered or swapped out for a custom implementation.
As an example, given labeled tuple pairs such as the following:
DeepMatcher uses labeled tuple pairs and trains a neural network to perform matching, i.e., to predict match / non-match labels. The trained network can then be used to obtain labels for unlabeled tuple pairs.