Offline User Recommendation via Video Attribute Analysis
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Solution Overview
Problem
Traditional offline object recommendation modes fail to accurately recommend objects based on user characteristics, leading to inaccurate recommendations and a suboptimal user experience.
Innovation Solution
An information sending method that analyzes video data of offline users to determine their attributes and matches them with historical access information of online users, recommending objects based on the online users' preferences, thereby improving the accuracy of offline object recommendations by combining online and offline data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional offline recommendation modes are used, then device complexity is low, but recommendation accuracy deteriorates
Solution Approach 1:
The patent merges online user data (historical access information, preferences) with offline user data (face attributes, video data) to create a unified recommendation system. This combination allows the system to leverage the accuracy of online big data while incorporating real-time offline user characteristics, thereby improving recommendation accuracy without requiring completely new complex infrastructure
Solution Approach 2:
The patent introduces an intermediary processing layer that includes a user attribute determination module and a recommendation module. This intermediary layer processes and matches online user data with offline video data, acting as a mediator that bridges the gap between simple offline systems and complex online systems, enabling accurate recommendations while managing system complexity
2Measurement precision
If offline video data is collected and analyzed, then recommendation accuracy is improved, but user privacy protection deteriorates
Solution Approach 1:
The patent extracts only the necessary user attributes (face attributes, demographics) from the collected video data for recommendation purposes, rather than storing or processing all raw video information. This extraction approach minimizes privacy intrusion while maintaining recommendation accuracy by using only the essential identifying features
Solution Approach 2:
The patent uses face attribute information as a simplified copy or representation of user identity, rather than storing or processing actual video footage or personal identifiers. This allows the system to match offline users with their online profiles and recommendation histories without handling sensitive personal data, thereby protecting user privacy while maintaining recommendation accuracy
Data Source
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AI summary
A method, apparatus and system for sending information, and a computer-readable storage medium, which relate to the technical field of computers . The method comprises : analyzing video data of an offline user, and determining an attribute of the offline user (S102); searching for historical access information of at least one online user matching the attribute of the offline user (S104); and determining, according to the historical access information of the various online users, an object recommended to the offline user, and sending information of the object to the offline user (S106).