Personalized News Engine Using Location-Based Source Filtering
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Solution Overview
Problem
Existing news personalization systems rely heavily on content-based features and declared user interests, failing to effectively capture the complex preferences of users, particularly the strong correlation between geographic location and preferred news sources, leading to a suboptimal news delivery experience.
Innovation Solution
A personalized news engine that identifies preferred news sources by analyzing user profile data, including geographic location, age, and interests, by grouping users with similar attributes and eliminating universally popular sources, to deliver news items primarily associated with the user's location, using a computing device with modules for input, analysis, and output to present relevant news.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If news personalization systems rely heavily on content-based features and declared user interests, then the system structure remains simple, but the system fails to effectively capture complex user preferences including geographic location correlations
Solution Approach 1:
The patent segments user profile data into multiple dimensions including geographic location, age, gender, and declared interests. By dividing the user characterization into distinct segments, the system can capture complex preferences more accurately without creating an unmanageably complex monolithic structure. Each segment can be processed independently to contribute to overall personalization.
Solution Approach 2:
The patent introduces geographic location as an additional dimension for news personalization, moving beyond traditional content-based and declared-interest approaches. This dimensional expansion allows the system to capture location-based preferences that were previously inaccessible, improving measurement precision by operating in a higher-dimensional user profile space.
2Measurement precision
If the system eliminates universally popular sources to identify location-specific preferred sources, then news personalization accuracy improves, but the quantity of available news sources decreases
Solution Approach 1:
The patent applies local quality by eliminating universally popular sources and focusing on sources that are specifically preferred by local user groups. Instead of treating all sources equally across all locations, the system identifies and prioritizes sources with local relevance, thereby improving news source selection accuracy for each geographic region while maintaining an appropriate quantity of locally-relevant sources.
3Measurement precision
If the system analyzes user logs and groups users by similar attributes, then user preference identification improves, but the computational processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing user log data into structured profiles with identified attributes such as geographic location, age, and interests. By preparing this data structure in advance, the system reduces the computational burden during real-time news selection, thereby improving user group identification accuracy while minimizing additional processing time during actual news delivery.
Data Source
AI summary
News search and browse experience is personalized based on user preferences. User attributes like a geographic location are obtained and news sources preferred by other users with attributes similar to those of a requesting user are identified. News sources that are popular across different user groups are eliminated and relevant news items from the remaining news sources are retrieved and presented to the requesting user.