Implicit Profile Peer Relevancy Algorithm for Community Forums
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Solution Overview
Problem
Existing systems for matching peers in online communities often result in too many irrelevant potential matches, leading to wasted time and effort for users seeking expert advice, as they struggle to find responsive and relevant experts, which hampers the health and dynamism of community forums.
Innovation Solution
A peer directory system that utilizes an implicit profile and a peer relevancy algorithm to automatically route questions to the most relevant experts based on weighted matches across categories like initiative, vendor, OS, industry, and firm size, while considering past connection responses, to increase engagement and response rates in community forums.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional matching systems provide many potential matches to users, then users have more options to choose from, but users spend excessive time sorting through irrelevant matches and the overall match quality decreases
Solution Approach 1:
The patent replaces manual sorting and filtering mechanisms with an automated relevance scoring system that uses machine learning algorithms to rank potential matches. The system automatically calculates relevance scores based on multiple factors including profile compatibility, interaction history, and community feedback, eliminating the need for users to manually evaluate each potential match.
Solution Approach 2:
The patent introduces a relevance score parameter that quantifies the compatibility between users and potential matches. By changing the matching system from a simple list of options to a ranked list based on calculated relevance scores, the system automatically filters out low-quality matches while preserving diverse options, thus reducing user time investment while maintaining adaptability.
2Measurement precision
If users manually evaluate each potential match to find the best fit, then match quality may improve, but the process becomes extremely time-consuming and users may settle for less relevant matches
Solution Approach 1:
The patent performs preliminary evaluation of all potential matches before presenting them to users. The system pre-calculates relevance scores, checks compatibility criteria, and ranks matches in advance, so that users receive a pre-filtered, pre-ranked list where the most relevant matches appear first. This eliminates the need for users to conduct their own time-consuming evaluations.
Solution Approach 2:
The patent creates a simplified representation of complex match evaluation criteria through relevance scores. Instead of requiring users to manually assess multiple dimensions of compatibility, the system copies and processes these evaluation criteria algorithmically, producing a single relevance score that captures the essence of match quality without requiring user time investment.
3Productivity
If the system provides automated matching with high relevance scores, then users receive better matches quickly, but the system complexity and computational resources increase
Solution Approach 1:
The patent divides the complex matching process into separate modular components: profile parsing modules, compatibility calculation modules, ranking modules, and filtering modules. Each component handles a specific aspect of the matching process independently, making the overall system more manageable and maintainable despite the increased computational requirements.
Solution Approach 2:
The patent introduces relevance scores as an intermediary representation that bridges complex compatibility calculations and simple user presentation. Instead of directly comparing user profiles and generating matches, the system first computes relevance scores as intermediate values, which then serve as the basis for ranking and filtering. This intermediary layer simplifies the overall system architecture while enabling sophisticated matching logic.
4Reliability
If community managers manually answer questions to maintain community health, then community dynamics are preserved, but the process is manual and time-intensive
Solution Approach 1:
The patent enables the community forum to serve itself through automated matching systems that connect questioners with appropriate responders based on their profiles and expertise. The system automatically identifies suitable community members, ranks them by relevance, and facilitates connections without requiring manual intervention from community managers, thus maintaining community dynamics while eliminating time-intensive manual processes.
Data Source
AI summary
Methods and systems for creating an implicit profile for use by a recommendation engine or a question router is provided. User behavior on at least one of one or more electronic devices and an electronic communications network is tracked. User-related information relating to the user behavior is analyzed to extract or derive key words therefrom. The key words are stored in a profiles database as the implicit profile and used by the recommendation engine or question router to characterize user interests, expertise, and skills when matching a request from a querying user to a potential user or group of users having the relevant background to respond to the request.