A server 4 executes a similarity calculation step (S2) of calculating similarity between content of one document and content of another document, a cluster classification step (S3) of generating a network in which a document is set as a node based on calculated similarity and similar nodes are connected by an edge, and performing classification based on similar documents, a first index calculation step (S4) of calculating a first index indicating centrality of a document in the network, a second index calculation step (S5) of calculating a second index that is different from the first index in the network and indicates importance of a document, and a display data generation step (S6) of generating, regarding a document, first display data indicating the network by an expression of a size of an object of a node according to the first index, an expression of a gauge having a shape corresponding to a shape of the object according to the second index and a length of the gauge, an expression according to a type of the cluster, and an expression according to magnitude of similarity between documents.

A method for screening documents. The order of the text in the documents can be changed in order to create additional documents. A vocabulary of words from the text in the documents can be built. The words can be coded as vectors. Vector relationships can be defined. The documents can be classified using the vector relationships.

A method for screening documents. The order of the text in the documents can be changed in order to create additional documents. A vocabulary of words from the text in the documents can be built. The words can be coded as vectors. Vector relationships can be defined. The documents can be classified using the vector relationships.

Techniques performed by a computing device are provided. A method includes (a) locating, by the computing device, a portion of a digital image that depicts fields of a paper form, the fields including markings; (b) identifying, by the computing device, a marking within one of the fields of the paper form as being contrary to a set of rules; and (c) modifying, by the computing device, the digital image to remove the identified marking from the digital image, so that the portion of the digital image depicts the one field of the paper form as being unmarked. An apparatus and computer program product for performing a similar method are also provided.

Disclosed herein are systems and methods for immunity data creation and immunity monitoring (e.g., management, maintenance, etc.). A user may upload immunity and redaction data. A community of other users may verify the uploaded data. A venue may comprise a target immunity level and an actual immunity level. Combining the verified uploaded data with the actual immunity level may yield a new actual immunity level. The user may be allowed to enter the venue if the new actual immunity level is at or above the target immunity level.

An Artificial Intelligence (AI) based document digitization, transformation and validation system extracts fields from digital documents via different document digitization processes. A document packet with a plurality of documents is initially accessed and any non-digital documents in the document packet are digitized. The errors in the digitized documents are corrected and non-English documents are translated into English. Each of the documents is provided to a plurality of digitization services for the extraction of fields by a plurality of field extraction models. If a field has multiple field instances extracted by more than one digitization service, then a field instance with the highest confidence score is selected for inclusion into the consolidated results. The consolidated results produced in different JavaScript Object Notation (JSON) formats are converted into a common JSON format which may be further validated and provided to downstream processes.

Systems, computer program products, and methods are described herein for the generation of an interface for upload and remote acceptance of a data file. The present invention may be configured to receive a request from a user to transfer resources associated with a document and certain user information from the user device. The document and/or the user may be associated with a supporting document. The present invention may be further configured to generate an interface comprising a triggered prompt for resource information, a triggered prompt for one or more data files containing the document, and a triggered prompt for one or more data files containing the supporting document. The present invention may be further configured to generate a request folder associated with the request. The request folder may contain the resource information, user information, the data files associated containing the document, and the data files containing the supporting document.

The present disclosure describes a value referred to as a compound object that stores multiple values in a single cell, wherein those multiple values are organized according to a defined structure. The compound object may store multiple values according to a known defined data structure such as, for example, a record, vector, matrix, table, or array. In other embodiments, the compound object may store multiple values as any nested combination of any one of the known or user-defined data structures. Each of the values stored in the compound object are individually referenceable and can fully participate with spreadsheet functionality including calculations, referencing, and formatting.

The present disclosure describes a value referred to as a compound object that stores multiple values in a single cell, wherein those multiple values are organized according to a defined structure. The compound object may store multiple values according to a known defined data structure such as, for example, a record, vector, matrix, table, or array. In other embodiments, the compound object may store multiple values as any nested combination of any one of the known or user-defined data structures. Each of the values stored in the compound object are individually referenceable and can fully participate with spreadsheet functionality including calculations, referencing, and formatting.

Potentially fraudulent documents can be identified automatically and flagged for further review. Document fraud detection can include a number of fraud detection tests, where if the document fails any of the tests, the document can be flagged for further review. Various tests can be performed that seek to determine whether a document has been altered. In one instance, a financial instrument can be scanned and analyzed to identify one or more layers associated with the financial instrument from a scanned representation, and a check of transaction details can be triggered when the financial instrument is associated with multiple layers.