Abstract: A method, system, and computer program product is provided for tokenizing document citations. The method may include tokenizing each string of a plurality of strings into at least one citation token representing at least one citation parameter, resulting in a plurality of citation tokens, grouping the plurality of citation tokens into a plurality of token groups, each token group of the plurality of token groups including at least one citation token representing a separate citation in the at least one textual document, assigning metadata to each token group of the plurality of token groups, and generating a normalized citation for each token group of the plurality of token groups based on the metadata.

Abstract: Provided are systems, methods, and computer program products for searching a plurality of documents based on a text string. The system includes at least one processor programmed or configured to identify a plurality of documents including a plurality of document types, each document of the plurality of documents including a document type, receive a text string based on user input, generate, with a machine-learning model, an ordered list of document types based the text string, search the plurality of documents for the text string to identify a subset of documents based on similarity between the text string and each document of the subset of documents, rank the subset of documents based at least partially on the similarity, a document type of each document of the subset of documents, and the ordered list of document types, and generate a graphical user interface based on the ranked list of documents.

Abstract: Provided are systems, methods, and computer program products for representing a plurality of events in an interactive graphical user interface. The system includes at least one processor programmed or configured to parse at least one textual document to identify a plurality of events related to at least one entity, determine a temporal parameter for each event of the plurality of events based on the at least one textual document, order the plurality of events into a sequence based on the temporal parameter for each event, and generate an interactive graphical user interface comprising a visual representation of the plurality of events on a user device based on the sequence, the visual representation of the plurality of events linked to a textual document of the at least one textual document.

Abstract: A method, system, and computer program product is provided for tokenizing document citations. The method may include tokenizing each string of a plurality of strings into at least one citation token representing at least one citation parameter, resulting in a plurality of citation tokens, grouping the plurality of citation tokens into a plurality of token groups, each token group of the plurality of token groups including at least one citation token representing a separate citation in the at least one textual document, assigning metadata to each token group of the plurality of token groups, and generating a normalized citation for each token group of the plurality of token groups based on the metadata.

Abstract: Provided are systems, methods, and computer program products for inserting citations into a textual document. The method includes receiving a first user input identifying a portion of a textual document, generating a plurality of predicted citations based on comparing at least one string in the textual document associated with the portion of the textual document to at least a subset of source documents of a plurality of source documents with a model selected from a plurality of models based on the at least one string, each predicted citation of the plurality of predicted citations corresponding to at least one source document of the plurality of source documents, displaying, on a graphical user interface, the plurality of predicted citations, and inserting a predicted citation of the plurality of predicted citations into the portion of the textual document based on a second user input.

Abstract: A method, system, and computer program product is provided for tokenizing document citations. The method may include tokenizing each string of a plurality of strings into at least one citation token representing at least one citation parameter, resulting in a plurality of citation tokens, grouping the plurality of citation tokens into a plurality of token groups, each token group of the plurality of token groups including at least one citation token representing a separate citation in the at least one textual document, assigning metadata to each token group of the plurality of token groups, and generating a normalized citation for each token group of the plurality of token groups based on the metadata.

Abstract: A method, system, and computer program product is provided for tokenizing document citations. The method may include tokenizing each string of a plurality of strings into at least one citation token representing at least one citation parameter, resulting in a plurality of citation tokens, grouping the plurality of citation tokens into a plurality of token groups, each token group of the plurality of token groups including at least one citation token representing a separate citation in the at least one textual document, assigning metadata to each token group of the plurality of token groups, and generating a normalized citation for each token group of the plurality of token groups based on the metadata.

Abstract: A computer parses the document to identify a citation, where the citation serves as a pointer to a source reference. The computer determines a location in the document of a textual assertion associated with the citation. The computer calculates relevancy scores between the textual assertion and a corresponding source reference and between the textual assertion and at least one alternate source reference, where the relevancy scores are determined based at least in part on a machine learning algorithm trained with a plurality of training samples. The computer generates a suggested list of at least one of the source references or at least one alternate source reference based on the relevancy scores calculated by the machine learning algorithm and adds a training sample to the plurality of training samples of the machine learning algorithm in response to an action by a user responsive to the suggested list.