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 method for retrieving an image-text block from a web page is provided, which comprises: retrieving an image node; filtering the image node to obtain candidate image nodes; traversing, for each of the candidate image nodes, a node in sequence toward an ancestor node of the candidate image node in a preset maximum traversal depth until an ancestor node with a text is visited, using the ancestor node with the text as a candidate image-text block; clustering the candidate image-text blocks based on hash values of the path information of the candidate image-text blocks; and determining, for each image-text block cluster, a common ancestor node of the candidate image-text blocks within the image-text block cluster based on the path information of the candidate image-text blocks, and determining path information of the image-text block cluster based on the common ancestor node.

Techniques and systems for collaborative document editing and generating feedback on draft documents are described. A draft document is shared with multiple readers in a file format that is the same or similar to the file format in which the document will be published. The readers provide comments on the draft document. The comments can be stored in the same file as the document. Feedback may be solicited from a reader based on reading activity while interacting with the document.

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.

Devices and a method are provided for providing feedback to a user. In one implementation, the method comprises obtaining a plurality of images from an image sensor. The image sensor is configured to be positioned for movement with the user's head. The method further comprises monitoring the images, and determining whether relative motion occurs between a first portion of a scene captured in the plurality of images and other portions of the scene captured in the plurality of images. If the first portion of the scene moves less than at least one other portion of the scene, the method comprises obtaining contextual information from the first portion of the scene. The method further comprises providing the feedback to the user based on at least part of the contextual information.

A document processing system processes documents including typewritten and/or handwritten data by converting them to document images for entity extraction. A received document is initially processed to generate a deep document data structured and for classification as one of a structured or an unstructured document. If the document is classified as a structured document, it is processed for entity extraction based on a matching template and image alignment of the document image with the matching template. If the document is classified as an unstructured document, entities are extracted by obtaining nodes and providing the nodes to a self-supervised masked visual language model.

A method for processing content in an electronic device and an electronic device for doing the same are provided. The method includes acquiring content including at least one character, and performing at least one of classifying the acquired content into at least one of a plurality of categories by analyzing the acquired content or generating vector images including a vector image corresponding to the at least one character based on the acquired content and displaying at least a part of the vector images on a display functionally connected to the electronic device.

Devices and a method are provided for providing feedback to a user. In one implementation, the method comprises obtaining a plurality of images from an image sensor. The image sensor is configured to be positioned for movement with the user's head. The method further comprises monitoring the images, and determining whether relative motion occurs between a first portion of a scene captured in the plurality of images and other portions of the scene captured in the plurality of images. If the first portion of the scene moves less than at least one other portion of the scene, the method comprises obtaining contextual information from the first portion of the scene. The method further comprises providing the feedback to the user based on at least part of the contextual information.

For the determination of an image series from a set of a number of image series, in each case of a signature is compiled for each of the number of image series. This signature is formed from a set of attributes of the respective image series. A signature from the signatures for the image series is ascertained that is most similar to a prespecified signature set. An action is performed with the image series whose signature was ascertained as the most similar signature.

Devices and a method are provided for providing feedback to a user. In one implementation, the method comprises obtaining a plurality of images from an image sensor. The image sensor is configured to be positioned for movement with the user's head. The method further comprises monitoring the images, and determining whether relative motion occurs between a first portion of a scene captured in the plurality of images and other portions of the scene captured in the plurality of images. If the first portion of the scene moves less than at least one other portion of the scene, the method comprises obtaining contextual information from the first portion of the scene. The method further comprises providing the feedback to the user based on at least part of the contextual information.