Web Content Enrichment via Keyword-Based Supplemental Embedding
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Solution Overview
Problem
Textual web content often struggles to engage readers for extended periods due to its lack of visual appeal and relevance, making it difficult to attract and retain visitors, and existing methods of modifying content are labor-intensive and inefficient.
Innovation Solution
A web server system that analyzes digital text content for keywords, matches them with supplemental content from other web pages, and embeds this supplemental content within the original text, enhancing the content without altering its structure or deleting the original material, thereby improving engagement and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If textual web content is used, then the content can be easily created and transmitted, but the reader engagement and attention span deteriorate
Solution Approach 1:
The patent combines multiple types of content (textual content from the target web page and supplemental content from source web pages) into a single enriched web page. The content enrichment module merges relevant supplemental content with the original textual content, creating a hybrid content format that maintains the ease of textual content creation while significantly improving reader engagement and attention span through diversified content presentation.
Solution Approach 2:
The patent creates composite web page content by integrating different content types (text, supplemental information, embedded content) into a unified structure. The enriched web page functions as a composite information structure that combines the simplicity of textual content with the engagement qualities of multi-format content, thereby extending reader attention span while preserving content creation ease.
2Reliability
If supplemental content is embedded within original content, then content relevance and engagement improve, but content complexity increases
Solution Approach 1:
The patent introduces a content enrichment module as an intermediary component that automatically manages the integration of supplemental content. This module acts as a mediator between the original web page content and external source web pages, automatically selecting, extracting, and embedding relevant supplemental content. This intermediary approach maintains content relevance while shielding the overall system from excessive complexity by automating the content integration process.
Solution Approach 2:
The content enrichment module operates autonomously to identify, extract, and embed relevant supplemental content without requiring manual intervention. The system self-manages the complexity of content integration by automatically analyzing source web pages, determining relevance based on keywords and content analysis, and seamlessly embedding supplemental content within the original content structure, thereby maintaining relevance while minimizing structural complexity.
3Productivity
If automatic content harvesting is implemented, then data collection efficiency improves, but the need for manual navigation and verification increases system complexity
Solution Approach 1:
The patent replaces manual navigation and data collection methods with an automated content harvesting system. The harvesting module uses programmatic approaches to automatically navigate web pages, extract content, and collect data without requiring manual intervention. This substitution of mechanical/manual processes with automated systems significantly improves data collection efficiency while the modular architecture manages the resulting system complexity.
Solution Approach 2:
The content harvesting module autonomously performs data collection tasks by automatically navigating source web pages, extracting relevant content, and storing it for later enrichment processes. The system self-manages the complexity of automated harvesting through modular design, where the harvesting module independently handles navigation, extraction, and data management, improving productivity while containing system complexity within discrete functional units.
Data Source
AI summary
Provided are a system and method for modifying textual web content of a web page by adding supplemental textual web content from another web page. In one example, the method includes analyzing a body of digital text content from a web page and determining at least one keyword included within the body of the digital text content, matching the at least one keyword with supplemental web content from another web page previously auto-detected by the web server, modifying the body of digital text content by embedding supplemental digital text content from the supplemental web content within the body of the digital text content, and transmitting the supplemental digital text content to a computing device providing the web page.