Profile Personalization Based on Viewer Relevance
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Solution Overview
Problem
Social networking platforms lack effective methods to personalize member profiles based on viewer information, failing to highlight relevant attributes that could enhance engagement and connection between members.
Innovation Solution
A social networking system that uses an algorithm to rank member attributes based on relevancy to the viewer, emphasizing entity, network, and event attributes by calculating an overall score, and presenting these as profile highlights to capture the viewer's attention, allowing for recommended actions such as messaging or emailing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If member profiles display all available attributes, then completeness of information is improved, but viewer engagement and attention capture deteriorate due to information overload
Solution Approach 1:
The patent extracts and highlights only the most relevant member attributes based on viewer characteristics, separating critical information from the full profile. The system identifies and presents key attributes (such as skills, education, or work experience) that are most pertinent to the specific viewer, rather than displaying all attributes equally.
Solution Approach 2:
The patent applies different presentation qualities to different profile attributes based on their relevance to the viewer. High-relevance attributes receive prominent placement and enhanced visualization (profile highlights), while less relevant attributes are presented in standard format. This creates a differentiated presentation strategy that optimizes viewer attention.
2Ease of operation
If profile attributes are personalized based on viewer information, then viewer engagement is improved, but system complexity increases due to algorithm requirements
Solution Approach 1:
The patent changes the parameter of attribute relevance by calculating relevance scores based on viewer characteristics and attribute importance. The system dynamically adjusts which attributes are highlighted by computing relevance metrics that consider the viewer's profile, the member's attributes, and the context of the viewing situation.
Solution Approach 2:
The system performs self-service by automatically generating personalized profile presentations without requiring manual intervention. The algorithm autonomously identifies relevant attributes, calculates relevance scores, and configures the profile highlight section based on viewer-member compatibility.
3Productivity
If relevant attributes are highlighted to capture viewer attention, then connection formation is improved, but processing time increases due to algorithm calculations
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and caching attribute relevance scores and viewer-member compatibility metrics. The system prepares relevance data in advance, storing computed values that can be quickly retrieved and applied when viewers access profiles, rather than performing full calculations in real-time.
Data Source
AI summary
Techniques for presenting a personalized member profile page to a viewer are described. A highlight module can receive a request to view a profile page of a member in a social network. The highlight module can access viewer data of a viewer associated with the request, and access member data of the member. Additionally, the highlight module can determine a plurality of member attributes relevant to the viewer based on the viewer data, the plurality of member attributes being derived from the member data. Furthermore, the highlight module can calculate an overall score for a member attribute in the plurality of member attributes based on the viewer data and the member data. Subsequently, a profile generation module can cause a presentation, on a display of a device, of the member attribute on the profile page, when the overall score of the member attribute is higher than a predetermined threshold value.