Browser Content Recommendation System Using Geographical and Behavioral Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current browser technologies fail to provide personalized content recommendations that effectively enhance user experience by considering geographical location, historical user behavior, and numerical scores, leading to suboptimal user engagement and frequent usage.
Innovation Solution
A method and device for recommending content to a browser that combines popular content from the user's geographical area, content related to historical user behavior, and content based on user numerical scores, using click-through rates to determine the relevance and display these in an order of clicks within a unit time, with the option to skip or differently present browsed content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If content recommendation considers multiple factors (geographical area, historical behavior, user scores), then user experience and click-through rate are improved, but system complexity increases
Solution Approach 1:
The patent segments the content recommendation system into three independent modules: geographical area module, historical behavior module, and user score module. Each module processes specific data independently and contributes to the final recommendation, making the complex system manageable and maintainable while achieving comprehensive user experience optimization
Solution Approach 2:
The patent merges the outputs of three separate recommendation modules (geographical, historical behavior, and user score) into a unified recommendation result. This combination allows the system to leverage multiple data dimensions simultaneously, improving recommendation accuracy and user experience without requiring a single overly complex algorithm
2Productivity
If content is personalized based on user behavior and preferences, then user engagement increases, but data processing requirements increase
Solution Approach 1:
The patent extracts only the most relevant features from user data (geographical location, key historical behaviors, and user scores) rather than processing all available data. This selective extraction reduces data processing volume while maintaining high user engagement through personalized recommendations
Solution Approach 2:
The patent implements partial action by focusing on three specific dimensions of user data rather than comprehensive analysis. This partial approach to data processing achieves effective personalization and high user engagement without the computational burden of analyzing all possible user attributes
Data Source
AI summary
The present disclosure discloses a method and a device for recommending content to a browser of a terminal device and a method and a device for displaying recommended content on a browser of a terminal device. The method for recommending content to a browser of a terminal device includes: recommending content to a browser of a terminal device, where the content includes a first quantity X of popular content of a geographical area to which the terminal device currently belongs, a second quantity Y of content related to a historical user behavior of a user of the browser of the terminal device, and a third quantity Z of content related to a user numerical score of the browser of the terminal device. According to the present disclosure, content matching a browsing interest and habit of a user may be provided, to obtain a relatively high user click-through rate and desirable browsing experience.