URL Recommendation Engine Using Click Aggregation and Encoding
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Solution Overview
Problem
It is challenging to effectively track and analyze the sharing and forwarding of content across multiple users, devices, and sources due to the complexity of user interactions with digital content on the internet.
Innovation Solution
The system employs techniques to identify, track, and analyze user interactions by assigning relevance scores to digital resources based on user actions, such as clicks and shares, and provides methods to identify trending phrases and user influence, as well as generate recommended lists of URLs based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system tracks and analyzes user interactions across multiple users, devices, and sources, then the ability to identify and recommend relevant content is improved, but the complexity of tracking and analyzing such interactions increases
Solution Approach 1:
The system segments the complex tracking task by creating separate click trackers for different URL encodings and maintaining distinct click lists for each user. This division allows the system to handle multiple users and devices independently, reducing the overall complexity while maintaining comprehensive tracking capability.
Solution Approach 2:
The patent introduces encoded URLs as intermediaries between the original URLs and the tracking system. By encoding URLs with unique identifiers and using these encoded versions as mediators in the tracking process, the system simplifies the analysis of user interactions while preserving the ability to trace clicks across multiple users and devices.
2Measurement precision
If the system generates recommended URL lists by aggregating multiple enumerated lists, then the accuracy of content recommendations is improved, but the computational resources and time required increase
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing click lists for each user based on their click history. These pre-computed lists are stored and can be quickly retrieved and aggregated when generating recommendations, avoiding the need to re-analyze all historical data each time recommendations are needed.
Solution Approach 2:
The patent merges multiple click lists from different users and URL encodings to generate comprehensive recommendation lists. By combining these pre-computed lists through aggregation operations, the system achieves high recommendation accuracy without processing individual click events from scratch.
3Adaptability or versatility
If the system monitors clicks on encoded URLs to generate user profiles and recommendations, then the personalization of content delivery is improved, but the data processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for personalization by maintaining click lists that record which URLs each user has clicked. Rather than storing and processing all raw interaction data, the system extracts and retains only the click patterns necessary for generating personalized recommendations.
Solution Approach 2:
Instead of building comprehensive user profiles from all possible interaction data, the system inverts the approach by using simple click lists on encoded URLs as the foundation for personalization. This inverted approach achieves effective personalization with minimal data processing requirements.
Data Source
AI summary
The present disclosure is directed to a method for providing a recommended list of uniform resource locators (URLs) responsive to a uniform resource locator (URL). The method may include identifying, by a server, a plurality of users that clicked on an encoded uniform resource locator (URL) link corresponding to a URL. The server may identify a plurality of encoded URL links clicked by each of the plurality of users. The server may determine a number of users who clicked on each encoded URL link of the plurality of encoded URL links and also clicked on the encoded URL link. The server may enumerate, responsive a request comprising the URL, a list of URLs and their corresponding score based on the determination, each URL of the list of URLs corresponding to one of the plurality of encoded URL links.