Personalized Educational Search Ranking System
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Solution Overview
Problem
The complexity of searching for educational material is exacerbated by the diversity of online content providers, which often require different interactions and indexing methods, making it difficult to integrate and rank search results effectively.
Innovation Solution
A system that combines search results from both real-time and static sources using a processor to determine a unified set of search results, sorted based on personalized relevance scoring, which includes local and Internet search results, and filters them according to customer preferences and engagement factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If search results are integrated from multiple diverse content providers, then comprehensiveness of search results is improved, but complexity of integrating and ranking results worsens
Solution Approach 1:
The patent introduces an intermediary ranking system that mediates between diverse content providers and the user. This intermediary applies standardized ranking signals (engagement metrics, recency, authority) to normalize results from different sources, enabling comprehensive integration without direct complexity between providers and users.
Solution Approach 2:
The patent transforms diverse search results into a standardized parameter space by applying consistent ranking signals across all content providers. By changing the parameters used for evaluation (engagement metrics, recency, authority) into a unified framework, the system can integrate results from multiple sources without proportionally increasing integration complexity.
2Ease of manufacture
If traditional web page indexing methods are used, then simplicity of indexing is maintained, but effectiveness of searching educational material worsens
Solution Approach 1:
The patent applies local quality by treating educational content differently from traditional web content. Instead of using a uniform indexing approach, the system applies specialized ranking signals tailored to educational materials (engagement metrics, recency, authority) to specific content types, improving search effectiveness without requiring complete redesign of the indexing system.
3Adaptability or versatility
If content providers require different interactions and indexing methods, then diversity of content sources is maintained, but ease of operation worsens
Solution Approach 1:
The patent creates a universal ranking framework that can handle multiple content providers with different indexing methods. By designing a multi-functional ranking system that accepts various input formats and applies standardized evaluation criteria (engagement, recency, authority), the system maintains diversity of sources while providing a unified, easy-to-use interface for users.
Data Source
AI summary
A system for educational learning searching includes an input interface and a processor. The input interface is configured to receive a request to search for educational information. The processor is configured to determine a first set of search results from one or more real-time sources; determine a second set of search results from one or more static sources; determine a combined set of search results based at least in part on the first set of search results and the second set of search results; and provide the combined set of search results, wherein the combined set of search results is sorted based at least in part on personalized relevance scoring.