Abstract: The present invention concerns a method for transforming an unstructured set of data representing a standardized form to a structured set of data. The method comprises a processing phase comprising the steps of determining a plurality of data blocks in the unstructured set of data using learning parameters determined using a plurality of samples, each data block corresponding to a visual pattern on the standardized form and being categorized to a known class, of processing data in each data block and of forming a structured set of data using the processed data from each data block, according to the class of this block.

Abstract: The present invention concerns a method for transforming an unstructured set of data representing a standardized form to a structured set of data. The method comprises a processing phase comprising the steps of determining a plurality of data blocks in the unstructured set of data using learning parameters determined using a plurality of samples, each data block corresponding to a visual pattern on the standardized form and being categorized to a known class, of processing data in each data block and of forming a structured set of data using the processed data from each data block, according to the class of this block.

Abstract: There is provided a computer implemented method of transforming an unstructured set of data to a structured set of data. In some examples, the method comprises segmenting the unstructured set of data into segments, classifying each segment, extracting key terms from each segment using an extraction model, the extraction model selected from a plurality of extraction models based on the classification of the segment, generating the structured set of data using the segments and the extracted key terms.

Abstract: Provided is a system and method for processing contract documents. The method includes searching contract documents to form one or more groups of contract documents by selecting a first contract document for each group and searching for other contract documents having a relevance score within a relevance threshold. A most recently revised contract document is determined within each group and a similarity score determined for each contract document in the group against the most recently revised contract document for the group. Contract documents having a similarity score below a similarity threshold are removed from each group to form one or more respective filtered groups of contract documents. Contract documents of each filtered group are compared to determine a template for the filtered group.

Abstract: A computer implemented method and a computer system for reducing the duplication of data records in a database are provided. An identifier associated with a first entity and a data record associated with a second entity and comprising data stored therein are provided to a neural network. The neural network comprises a plurality of nodes each containing a learned parameter. The neural network applies the learned parameters of at least a subset of the plurality of nodes to data representative of the identifier and the data stored in the at least one data record. The respective learned parameters are used to identify whether the at least one data record contains data that satisfies a similarity threshold with respect to the data representative of the identifier. Responsive to identifying that the similarity threshold is satisfied, the neural network generates a link between the first entity and the second entity.

Abstract: Provided is a system and method for processing contract documents. The method includes parsing a first contract document to identify a plurality of clauses in the first contract document, each clause of the plurality of clauses including a sequence of words, generating a plurality of representation vectors based on the first contract document and at least one embedding model, wherein each representation vector of the plurality of representation vectors is generated based on a separate clause of at least a subset of clauses of the plurality of clauses, comparing each representation vector of the plurality of representation vectors with a second plurality of representation vectors stored in a vector database, and generating output data based on the representation vectors and the first contract document.

Abstract: The present invention concerns a method for transforming an unstructured set of data representing a standardized form to a structured set of data. The method comprises a processing phase comprising the steps of determining a plurality of data blocks in the unstructured set of data using learning parameters determined using a plurality of samples, each data block corresponding to a visual pattern on the standardized form and being categorized to a known class, of processing data in each data block and of forming a structured set of data using the processed data from each data block, according to the class of this block.

Abstract: Provided is a system and method for processing contract documents. The method includes searching contract documents to form one or more groups of contract documents by selecting a first contract document for each group and searching for other contract documents having a relevance score within a relevance threshold. A most recently revised contract document is determined within each group and a similarity score determined for each contract document in the group against the most recently revised contract document for the group. Contract documents having a similarity score below a similarity threshold are removed from each group to form one or more respective filtered groups of contract documents. Contract documents of each filtered group are compared to determine a template for the filtered group.

Abstract: Provided is a system and method for processing contract documents. The method includes parsing a first contract document to identify a plurality of clauses in the first contract document, each clause of the plurality of clauses including a sequence of words, generating a plurality of representation vectors based on the first contract document and at least one embedding model, wherein each representation vector of the plurality of representation vectors is generated based on a separate clause of at least a subset of clauses of the plurality of clauses, comparing each representation vector of the plurality of representation vectors with a second plurality of representation vectors stored in a vector database, and generating output data based on the representation vectors and the first contract document.