Multimedia Signature-Based User Preference Identification
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Solution Overview
Problem
Existing solutions for understanding user preferences are inaccurate due to users providing incomplete information, either actively or passively, due to privacy concerns, leading to inefficiencies in identifying and providing personalized recommendations.
Innovation Solution
A method and system that generate signatures for multimedia content elements, analyze user interactions, and match these signatures against user profiles to determine contextual insights and preferences, thereby providing accurate and personalized recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users actively provide information to specify their interests, then user preference identification is possible, but the information provided is incomplete and inaccurate due to privacy concerns
Solution Approach 1:
The patent introduces a passive tracking intermediary system that operates between users and the recommendation service. Instead of directly asking users for information, the system uses tracking agents to indirectly observe and collect user behavior data from multiple sources including social media, browsing history, and interactions. This intermediary approach allows comprehensive data collection without requiring direct user disclosure, thus maintaining information completeness while respecting user privacy concerns.
2Quantity of substance
If users provide information through social networks, then some user information is collected, but the information is limited and takes significant time to become useful
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing user data from multiple sources in advance. Tracking agents are deployed to gather information from social media platforms, browsing history, and other digital footprints before recommendations are needed. This preliminary data collection and processing eliminates the time delay that would otherwise occur when trying to gather sufficient information at the moment of recommendation generation.
Solution Approach 2:
The patent merges multiple data collection sources including social media profiles, browsing history, email communications, and interaction patterns into a unified user profile. By combining these diverse data streams through the tracking agent system, the platform accumulates comprehensive user information much faster than relying on a single source, thus reducing the time required to gather useful information for accurate recommendations.
3Loss of information
If passive tracking of user activity is implemented, then user information is collected over time, but the information remains limited due to privacy concerns
Solution Approach 1:
The patent transitions from traditional single-dimension tracking (explicit user inputs) to multi-dimensional passive tracking by deploying agents across multiple digital domains including social media platforms, browsing sessions, email interactions, and application usage. This dimensional expansion allows the system to collect comprehensive user information indirectly through various digital footprints, overcoming privacy-based limitations while maintaining high measurement precision through aggregated pattern analysis.
Data Source
AI summary
A system, method, and computer-readable medium for providing recommendations based on a user interest. The method includes: generating at least one signature for at least one multimedia content element; querying, based on the generated at least one signature, a user profile to identify the user interest related to the at least one multimedia content element; generating at least one contextual insight based on the user interest, wherein each contextual insight indicates a user preference; searching for at least one content item that matches the at least one contextual insight; and causing a display of the at least one matching content item as a recommendation.