Encoded URL Tracking System for Search Relevance
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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 scoring digital resources based on user actions, such as clicks and shares, and provides search results and trending phrases by aggregating user interactions, while also tracking user influence and recommending URLs based on interaction data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user interactions with digital content are tracked across multiple users, devices, and sources, then the ability to identify and analyze content sharing patterns is improved, but the system complexity and difficulty of tracking increases
Solution Approach 1:
The patent introduces an intermediary tracking system that mediates between users, devices, and content sources. This intermediary layer captures interaction data through encoded URLs and cookies, centralizing the tracking function and reducing the complexity burden on individual components while maintaining high tracking accuracy across the distributed system.
Solution Approach 2:
The tracking system is designed with universal functionality to handle diverse interaction types (clicks, shares, forwards) across multiple platforms and devices through a unified encoded URL mechanism. This multi-functional approach allows the same system architecture to track various content types and user actions without requiring separate tracking systems for each case.
2Measurement precision
If relevance scoring is performed based on aggregated user interactions, then the accuracy of search results is improved, but the computational time and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and aggregating user interaction data into structured formats during user activities. Interaction patterns are captured and stored in advance, allowing the relevance scoring algorithm to query pre-aggregated data rather than processing raw interaction logs in real-time, thus reducing computational time while maintaining scoring accuracy.
Solution Approach 2:
The patent replaces traditional mechanical search ranking methods with a data-driven relevance scoring system that uses aggregated interaction patterns. Instead of relying on manual or rule-based ranking, the system automatically computes relevance scores based on processed user behavior data, significantly reducing the time and computational resources required for accurate search result ranking.
3Loss of information
If user interaction data is collected and stored for analysis, then the ability to identify trending content and user influence is improved, but the data storage requirements and privacy concerns increase
Solution Approach 1:
The system extracts only the essential interaction data elements needed for analysis, such as encoded URL clicks, user identifiers, and interaction timestamps, while discarding redundant or unnecessary information. This selective extraction approach maintains the ability to identify trending content and user influence patterns while minimizing the volume of data that needs to be stored and managed.
Data Source
AI summary
The present disclosure is directed to providing search results based on user interaction with content. A server receives identification of a plurality of clicks of encoded uniform resource locator (URL) links and identifies, for each of the plurality of clicks, data about a user who clicked an encoded URL link and traffic data associated with a device from which the user clicked the encoded URL link. The server may store a record comprising data about the user and traffic data associated with each click. The server may determine, based on the records, a relevancy score for each content identified from decoding the encoded URL links. The server may communicate, responsive to receiving a request to search content based on a keyword, a set of search results based on the keyword and the relevancy score.