Relationship-Centric Communication Session Content Matching
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Solution Overview
Problem
Existing communication technologies do not effectively utilize shared interests and activities between participants during sessions to provide relevant content, leading to a lack of personalized and interactive experiences.
Innovation Solution
A method and apparatus that establish communication sessions between devices, determine mutual topics of interest by cross-referencing user interests, and retrieve content based on a content descriptor to display relevant resources simultaneously on both devices, using a lookup table to cross-reference content and interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic communication platforms are used, then broad compatibility is achieved, but personalized content delivery is lost
Solution Approach 1:
The system performs preliminary actions by pre-collecting user profile data, interests, and communication history before the actual communication session. This advance preparation enables rapid personalization during the session without adding real-time complexity, as the matching logic has already been prepared in advance based on stored user attributes.
Solution Approach 2:
An intermediary server acts as a mediator between communication devices, handling the complex tasks of profile matching, content selection, and personalized resource delivery. This intermediary absorbs the system complexity, allowing individual devices to remain simple while still achieving personalized content delivery through the mediating server's processing.
2Ease of operation
If communication sessions focus on basic connectivity, then system simplicity is maintained, but user engagement is reduced
Solution Approach 1:
The system implements self-service by automatically matching users based on their profiles and interests without requiring manual configuration. The communication session automatically receives personalized content and resources based on the system's analysis of user attributes, eliminating the need for users to manually set up personalized features while maintaining operational simplicity.
Solution Approach 2:
The system dynamically changes parameters such as content selection, resource allocation, and interface presentation based on user profiles and session context. These parameter adjustments occur automatically during the session, enhancing communication effectiveness without requiring users to change their interaction patterns or complicate the setup process.
3Loss of information
If content is customized for each user, then relevance is improved, but information processing time increases
Solution Approach 1:
The system performs preliminary content filtering and matching based on user profiles before the communication session begins. User interests, preferences, and historical data are pre-analyzed to create personalized content lists and resource recommendations, enabling rapid content delivery during the session without real-time processing delays.
Solution Approach 2:
The system creates and stores template-based content profiles and resource configurations in advance for different user types and communication scenarios. During actual sessions, these pre-created templates are copied and adapted rather than generated from scratch, significantly reducing content delivery time while maintaining personalization through template parameter adjustment.
Data Source
AI summary
A method for providing relationship-centric resources includes establishing a communication session between a first device and a second device, determining, during the communication session between the first and second devices, an intersection of mutual topics of interest between users of the first and second devices by cross-referencing sets of interests for the users, retrieving content based on a determination that the content meets a content descriptor, and simultaneously displaying the retrieved content. The content descriptor describes a nature of the communication session. The retrieving is further based on a determination that the content is related to a mutual topic of interest from the intersection of mutual topics of interest between the users of the first and second devices. The determination of relatedness is based on a cross-reference between the content and the mutual topic of interest. The cross-reference is stored in a lookup table.