Electronic Document Browsing via Interest Score Ranking
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Solution Overview
Problem
Existing electronic document browsing methods fail to replicate the experience of physically browsing through a document, as they lack the ability to assess and provide pages that are likely to capture a user's attention, unlike physical books or magazines.
Innovation Solution
A method and system that analyzes and scores content in electronic documents based on user interactions and metadata to determine the interest level of pages, allowing users to browse through ranked candidate pages that are likely to be of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a fixed number of pages is jumped ahead in an electronic document, then navigation speed is improved, but the browsing experience quality deteriorates because there is no assessment of page interest
Solution Approach 1:
The system pre-calculates and stores interest scores for all pages in the document before browsing begins. These scores are based on various factors such as content density, image presence, and text analysis. When a user requests to browse forward, the system immediately provides the next interesting page without needing to evaluate pages in real-time, thus maintaining both speed and quality.
Solution Approach 2:
The patent replaces the mechanical approach of sequentially flipping through pages or jumping fixed numbers of pages with an intelligent system that uses automated scoring and selection algorithms. The system automatically evaluates pages based on pre-established criteria and presents pages in an optimized sequence that simulates natural browsing behavior without manual page-by-page inspection.
2Ease of operation
If sequential page-by-page browsing is implemented in an electronic document, then browsing experience quality is improved by allowing page assessment, but navigation speed deteriorates
Solution Approach 1:
The system pre-calculates and stores interest scores for all pages in the document before browsing begins. These scores are based on various factors such as content density, image presence, and text analysis. When a user requests to browse forward, the system immediately provides the next interesting page without needing to evaluate pages in real-time, thus maintaining both speed and quality.
3Device complexity
If traditional electronic document navigation is used, then device complexity is reduced, but the ability to replicate physical browsing experience deteriorates
Solution Approach 1:
The system automatically analyzes document content and assigns interest scores to pages without requiring user input or configuration. The browsing algorithm autonomously determines the sequence of pages to present based on pre-established scoring criteria, making the system adaptable to different document types while maintaining relatively simple device architecture.
Solution Approach 2:
The system uses multiple parameters to evaluate page interest including content density, image presence, text length, and other document-specific features. By changing and weighing these parameters dynamically based on document type and user behavior patterns, the system achieves high adaptability without requiring complex device architecture.
Data Source
AI summary
A user's request for a page to be provided in response to a browse request is fulfilled by determining a candidate set of pages based on the page displayed on the client when the browse request is sent. Scores for those candidate pages are used to rank the candidate pages and a page is provided to the client based on the ranking of the candidate pages.