Adobe, Inc.

Mudit Rastogi

Souvik Sinha Deb

Gaurav Tarlok Kakkar

Prakhar Mehrotra

Arihant Jain

Ankur Murarka

Mohammad Javed Ali

Amit Gaurav

Abhinav Kumar Agarwal

Anshul Jain

Abhinav Kaushik

Damanpreet Kaur

An annotation corresponding to a first range of text of a first document may be received. Based on the annotation, comparisons may be performed between a text string that comprises the first range of text and a group of text of a second document at different positions in the group of text. Based on the comparisons, similarity scores between the text string and the group of text may be determined at the different positions in the group of text. A position for the annotation in the group of text may be selected based on the similarity scores at the different positions. The annotation may be associated with a second range of text in the group of text that corresponds to the position.

Mapping annotations to ranges of text across documents

Digital annotation and digital content linking techniques implemented by digital content generation system as part of a computing device are described. The system is configured to convert a digital document including an object from a first format to a second format, receiving the digital document in the second format with an annotation associated with the object, converting the digital document in the second format with the annotation associated with the object to the first format, and maintaining the association between the annotation and the object subsequent to an alteration in a page sequence of the document in the first format, or movement of the object.

Digital annotation and digital content linking techniques

Techniques are provided for a computer processor-implemented method of beautifying an electronic textual document having text organized in a plurality of sections. Each of the sections is representative of a corresponding one of a plurality of textual elements. The method includes: receiving a user selection of the text for beautification, the selected text including at least a portion of one of the sections; classifying the selected text as the corresponding one of the textual elements represented by the one of the sections; ranking a set of attributes applicable to the one of the textual elements; presenting an ordered list of the highest-ranked attributes; in response to receiving a selection of one or more of the presented attributes, applying the selected attributes to the selected text; and reranking the applicable attributes to reflect the selected attributes.

Document beautification using smart feature suggestions based on textual analysis

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Noida Uttar Pradesh, India

Mudit Rastogi