Edit Suggestions for Digital Documents via Automatic Element Parsing
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Solution Overview
Problem
Conventional content creation systems require technical knowledge from users to edit digital documents, inefficiently utilizing user and system resources, as they lack guidance on editable elements and their impact on the document's appearance.
Innovation Solution
A content editor application that automatically identifies editable page elements and provides a graphical user interface with edit suggestions, allowing users to edit without selecting elements, reducing the need for manual interaction and conserving system resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional content creation systems require manual user interaction to identify and edit elements, then users can edit digital documents, but users need considerable technical knowledge and time expenditure
Solution Approach 1:
The system automatically identifies editable page elements and generates edit suggestions without requiring user selection or technical knowledge. The processor autonomously parses the digital document, identifies editable elements based on performance data, and presents edit suggestions to the user, allowing the system to serve itself in the element identification task.
Solution Approach 2:
The system performs preliminary analysis of the digital document before user interaction by parsing the document structure, identifying editable elements, and generating edit suggestions in advance. This preliminary action prepares the edit suggestions menu ready for user review, eliminating the need for users to manually explore editable features.
2Ease of operation
If conventional systems provide manual editing capabilities, then users can edit digital documents, but system resources are excessively consumed responding to user input
Solution Approach 1:
The system performs all resource-intensive operations (parsing document structure, identifying editable elements, analyzing performance data, generating edit suggestions) before the user interacts with the interface. This preliminary processing eliminates the need for continuous system resource consumption during user exploration and interaction.
Solution Approach 2:
The system autonomously performs element identification and edit suggestion generation without requiring repeated user selections or system responses to user probing actions, thereby reducing overall system resource consumption while maintaining full editing capabilities.
3Adaptability or versatility
If conventional systems require user selection of page elements, then users can specify what to edit, but users need knowledge of which elements are editable
Solution Approach 1:
The system automatically identifies and presents editable page elements through the edit suggestions menu, eliminating the need for users to manually select elements or understand document structure. The system serves itself in identifying what can be edited based on performance data and document parsing.
Solution Approach 2:
The edit suggestions menu acts as an intermediary between the user and the document elements. Instead of users directly interacting with complex document structure, the intermediary menu presents simplified edit options that correlate to underlying elements, shielding users from technical complexity while maintaining editing control.
4Ease of operation
If conventional systems wait for user input to identify editable elements, then users can make selections, but processor and memory resources are unavailable for other tasks
Solution Approach 1:
The system performs element identification, document parsing, and edit suggestion generation as preliminary actions before user interaction begins. This upfront processing frees system resources for other computing tasks while still providing users with comprehensive editing capabilities when needed.
Data Source
AI summary
Techniques for generating edit suggestions for transforming digital documents are implemented in a digital medium environment. According to various implementations, a digital document is parsed to extract a digital page, and page elements of the digital page that are editable. A graphical user interface (GUI) is then output that identifies the page elements that are editable. The GUI, for instance, includes a suggestions menu with different edit suggestions that each correlate to different respective page elements. A user may then interact with individual edit suggestions to edit the different page elements, such as by adding, removing, or revising digital content of the page elements. The described techniques, for example, automatically identify editable page elements of a digital page and output edit suggestions for editing the page elements.


