Abstract: Systems and methods for performing logical semantic sentence comparisons and sentence-based searches. Training is performed by running an NLP pipeline on unstructured text comprising sentences and creating sentence matrix representations on the unstructured text; storing the matrix representations in an indexed database; combining the stored matrix representations; running an SVD on the combined matrix; storing the SVD components in the indexed database; reiterating through the output of the NLP pipeline the sentences of the unstructured training text to form a low-dimensional matrix conversion for each sentence for storage in the database based on the calculated SVD components. Subsequent query statements are run through the same process based and converted into low-dimensional matrix representations using the SVD components from training; the low-dimensionality query matrix is compared to the stored low-dimensional matrices to determine the closest relevant documents, that are returned to the user.

Abstract: Systems and methods for performing logical semantic sentence comparisons and sentence-based searches. Training is performed by running an NLP pipeline on unstructured text comprising sentences and creating sentence matrix representations on the unstructured text; storing the matrix representations in an indexed database; combining the stored matrix representations; running an SVD on the combined matrix; storing the SVD components in the indexed database; reiterating through the output of the NLP pipeline the sentences of the unstructured training text to form a low-dimensional matrix conversion for each sentence for storage in the database based on the calculated SVD components. Subsequent query statements are run through the same process based and converted into low-dimensional matrix representations using the SVD components from training; the low-dimensionality query matrix is compared to the stored low-dimensional matrices to determine the closest relevant documents, that are returned to the user.