User Need Prediction and Matchmaking for Trusted Recommendations
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Solution Overview
Problem
Users often rely on static information sources like websites and pamphlets for finding information about new cities, products, etc., which are not personalized or trusted, as they lack recommendations from relatable individuals with similar interests and experiences.
Innovation Solution
A system that uses a user need predictor, matchmaking service, and communications manager to identify and connect users with conversation assistance resources based on predicted needs, utilizing user profiles and signals to provide interactive and trusted recommendations from users with similar interests and experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static information sources like websites and pamphlets are used, then information availability is provided, but personalization and trustworthiness deteriorate
Solution Approach 1:
The patent introduces an intermediary system that connects users with relatable users who can provide personalized recommendations. This intermediary matches users based on shared characteristics, interests, and experiences, thereby transforming static information delivery into dynamic, trust-based interpersonal communication while maintaining information availability.
Solution Approach 2:
The system performs preliminary actions by pre-establishing user profiles that capture interests, experiences, and characteristics before the user actually needs information. This allows the matching system to proactively identify and connect users with relatable individuals, rather than relying on static information sources at the moment of need.
2Reliability
If relatable users are connected for personalized recommendations, then trustworthiness is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex task of finding reliable information into distinct functional modules: user profile creation, profile analysis, matching algorithm, and communication facilitation. Each module handles a specific aspect of the process, making the overall system more manageable and maintainable while delivering personalized, trustworthy recommendations.
Solution Approach 2:
The system creates universal user profiles that serve multiple functions: they enable matching with relatable users, provide basis for personalized recommendations, and facilitate future interactions. This multi-functionality reduces the need for separate systems for each task, thereby managing complexity while improving trustworthiness.
3Adaptability or versatility
If user profiles and signals are analyzed, then personalization is improved, but processing time increases
Solution Approach 1:
The system performs preliminary analysis of user signals and creates comprehensive user profiles in advance, before the user actually needs recommendations. This pre-processing allows the matching operation to be faster and more efficient when the user seeks information, reducing the perceived processing time while maintaining high personalization.
Solution Approach 2:
The matching system focuses analysis on locally relevant characteristics - specifically the aspects of user profiles that are most relevant to the current information need. Rather than re-analyzing entire profiles, the system identifies and compares only the pertinent local qualities, reducing processing time while maintaining personalization quality.
Data Source
AI summary
A conversation assistance resource system is provided to connected a user to a resource based on a predicted user need. The conversation assistance resource system monitors user signals relative to a user profile associated with the user. The user profile is based on previously received user signals and includes user preferences, interests, etc. A user need is predicted based on a received user signal. A resource is identified based on the predicted user need and the user profile relative to the resource profile. A communication channel is established between the user and the resource responsive to confirmation by the parties such that the user may query the resource to resolve the predicted user need.