A form compliance manager configured to create a policy graph corresponding to an electronic image of an offline form and a corresponding instruction set. The form compliance manager further configured to generate an electronically fillable form corresponding to the offline form and including at least a first context cue for a first field in the electronically fillable form. The first context cue can be based on a subgraph of the policy graph associated with the first field, and the subgraph can include field completion information for the first field, field value information for the first field, and field format information for the first field. The electronically fillable form configured to present the first context cue in response to selection of the first field.

An approach is provided in which the approach aggregates a set of pixel values from a bitmap image into a set of row sum values and a set of column sum values. The bitmap image is a pixelated representation of a document. The approach applies a localized Fourier transform to the set of row sum values and the set of column sum values to generate frequency representations of the set of row sum values and the set of frequency sum values. The approach decomposes the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations, and sends the set of image portions to a text recognition system.

A system to extract data from regions of interest on a document is provided. The system includes a storage device storing an image derived from a document having text information. The system includes a document importer operable to perform optical character recognition to convert image data in the image to machine readable data. The system includes a neural network that identifies at least one region of interest on the image to classify an area of the at least one region of interest as a table. The neural network is operable to take as input the machine readable data and the image and combine both the machine readable data and the image to determine that the classified area is the table.

Aspects of the present invention disclose a method for extracting information of an unlabeled image within a document and aligning the information to text of the document. The method includes one or more processors identifying an image that is not associated with a corresponding label in a document that includes text. The method further includes determining a feature of an object of the image. The method further includes identifying an alignment candidate of the text of the document based at least in part on the feature of the object, wherein the alignment candidate is a segment of the text of the document identified as corresponding to the feature of the object. The method further includes aligning the feature with the alignment candidate of the text of the document.

Embodiments for finding elements in optical character recognition (OCR) documents are provided. An indication of a selected portion of document is received. Salient pixels in the selected portion of the document are determined. Properties of the salient pixels in the selected portion of the document are identified. The properties of the salient pixels in the selected portion of the document are compared to properties of pixels in each of a plurality of portions of an OCR-converted version of the document. A cognitive analysis is utilized to select at least some of the plurality of portions of the OCR-converted version of the document as suspected matches to the selected portion of the document.

A computer-implemented method for digitizing a document, wherein the document has assigned a classification scheme may be provided. A digital image and an identifier of the classification scheme may be received, the image representing a portion of the document. A segmentation of the image may be determined into one or more image segments; for each of the image segments, content information may be captured from the image segment and a category may be assigned to the image segment, the category being selected from the classification scheme. One or more digitization segments may be selected from the segmentation. A graph model of the document may be populated, wherein each of the digitization segments is represented by a segment node of the graph model.

A computer system apparatus and a method carried out by such apparatus for interacting with a user via a behavior intervention designed to cause an increase in emotional well-being of the user. The behavior intervention has a plurality of conditions to be satisfied. The process includes receiving input data from the user during the behavior intervention, performing, on at least a portion of the received input data having text, semantic analysis to identify terms that satisfy the plurality of conditions and assessing, based on an amount of completeness of satisfying the plurality of conditions, a level of adherence to the behavior intervention. When one or more of the plurality of conditions are determined not as satisfied, the process includes generating a prompt designed to elicit, from the user, a response specific to satisfying the missing conditions.

An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.

A method of extracting meta-data from semi structured documents, by using area and cone orientation as relevance between words/phrases is described. It also a computer implemented system to handle OCR errors with respect to the coordinates interpreted for each word and user corrections both in online and offline mode. The method is carried out by the steps as follows: converting scanned or digital document to a readable format with coordinates using OCR; scanning the coordinates obtained through OCR for each character; marking all potential labels and values with a bounding box; searching for relevant labels for the particular value by using default control parameters and adjusting trainable parameters; mapping a cone region for the labels and values using the upper and lower angles along x-axis and the scope box and formulating the score area to get the confidence percentage which is used as measure to extract all relevant label-value pairs.

A form compliance manager configured to create a policy graph corresponding to an electronic image of an offline form and a corresponding instruction set. The form compliance manager further configured to generate an electronically fillable form corresponding to the offline form and including at least a first context cue for a first field in the electronically fillable form. The first context cue can be based on a subgraph of the policy graph associated with the first field, and the subgraph can include field completion information for the first field, field value information for the first field, and field format information for the first field. The electronically fillable form configured to present the first context cue in response to selection of the first field.