Social Routing Search Engine Connector for Precision and Completeness
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Solution Overview
Problem
Conventional search engines often return limited search results due to narrow query parameters, filtering out potential matches and failing to provide adequate results.
Innovation Solution
A search engine connector that utilizes social graph data to determine affinity and match metrics for users, routing content to increase interaction and affinity levels, and generating assessments to improve search results by connecting users with relevant content and interaction data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines use narrow query parameters to filter search results, then search precision is improved, but search completeness deteriorates
Solution Approach 1:
The patent segments search results into multiple categories including conventional keyword-matched results and socially-connected results. The system divides the search process into distinct pathways: traditional parameter-based filtering and social graph-based routing, allowing each segment to serve different purposes in balancing precision and completeness
Solution Approach 2:
The patent introduces social graph data as an intermediary layer between the query and search results. This intermediary uses affinity metrics and connection data to bridge the gap between narrow query parameters and potential search results, routing content through social connections to discover results that would otherwise be filtered out
2Quantity of substance
If search engines return all potential results without filtering, then search completeness is improved, but information relevance deteriorates
Solution Approach 1:
The patent changes the parameters used for result selection by incorporating social affinity metrics, connection strength, and interaction history alongside or instead of traditional keyword matching parameters. This allows the system to prioritize relevant results based on social context while maintaining completeness
3Productivity
If search engines actively route content based on social graph data, then user interaction is improved, but system complexity deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing affinity metrics, connection data, and social graph relationships in advance. This preparation work is done before search queries are submitted, allowing the complex social routing to occur efficiently during the actual search process without adding significant latency
Data Source
AI summary
Systems and methods for improving search results using social routing are provided. In example embodiments, an affinity metric and match metric are determined for a plurality of users. The affinity metric indicates an interaction level between a given user and the match metric indicates how well the given user matches parameters of a search string. Based on a correlation between the affinity metric and the match metric, one or more items of content may be transmitted to one or more selected users. Improved search results can then be generated based on interactions with the one or more items of content.