Multi-Level Summary Tree for Article Browsing
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Solution Overview
Problem
Current browsing methods, derived from traditional print media, are inefficient in quickly grasping and recalling the main points of articles in the era of information overload, as they lack innovative utilization of computer systems' capabilities.
Innovation Solution
A method that constructs graphical-browse-views based on multi-level summaries of articles, using natural language processing and user input to create point-by-point, simple-group, and compound-group summaries, enabling better visualization and recall through a hierarchical structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional table of contents and hyperlinks are used for browsing, then the browsing structure is simple to implement, but the time required to grasp main points is excessive
Solution Approach 1:
The patent segments the article content into multiple hierarchical levels (sections, subsections, paragraphs, sentences) and represents each segment as a node in a tree structure. This segmentation enables users to navigate to specific levels of detail, allowing rapid access to main points without reading the entire article, thus reducing time loss while maintaining manageable complexity through hierarchical organization.
Solution Approach 2:
The patent introduces a visual spatial dimension by displaying the hierarchical structure as a tree diagram with nodes positioned in two-dimensional space. This visual representation allows users to grasp the article structure and main points at a glance, transforming the traditional linear text browsing into a spatial visual exploration, significantly reducing the time required to understand article content.
2Loss of information
If detailed text content is displayed for browsing, then complete information is provided, but visual recall effectiveness is reduced
Solution Approach 1:
The patent applies local quality by displaying different amounts of information at different levels of the tree structure. Summary nodes contain condensed information suitable for quick overview and visual recall, while detailed nodes contain complete text content for those who need in-depth information. This localized differentiation allows users to choose their preferred level of detail, optimizing both information completeness and visual recall effectiveness according to their needs.
3Loss of information
If multi-level hierarchical structure is implemented, then information organization is improved, but the complexity of constructing the browsing view increases
Solution Approach 1:
The patent performs preliminary action by automatically analyzing the article content before display and pre-constructing the hierarchical tree structure with all nodes and relationships established in advance. This preprocessing step organizes the information into a ready-to-display format, reducing the complexity of real-time construction and enabling efficient multi-level information organization to be achieved through automated structural analysis rather than manual arrangement.
Data Source
AI summary
Disclosed is a method of generating a multi-level summary of an article. The method may comprise generating, by a computing device, a low-level summary from article-matter in an article. The method may also comprise generating, by the computing device, a mid-level summary based on the low-level summary and the article-matter. The method may also comprise generating, by the computing device, an upper-level summary based on the mid-level summary, the low-level summary, and the article-matter.