Network Traffic Bookmarking via Automated URL Indexing
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Solution Overview
Problem
Current HTTP traffic monitoring systems do not dynamically index content and associate tags with pages, limiting their ability to automatically identify and report interesting network resource identifiers based on network traffic patterns.
Innovation Solution
A networked data processing system that monitors HTTP traffic, detects network resource identifiers, and generates reports on popular URLs by tracking and indexing content, allowing for automated bookmarking and tagging of interesting URLs based on usage metrics and patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If HTTP traffic monitoring systems are used, then network traffic can be monitored, but the system cannot dynamically index content and associate tags with pages
Solution Approach 1:
The patent introduces a web crawler as an intermediary component that bridges network traffic monitoring and content indexing. The crawler dynamically accesses web pages, extracts content, and associates tags with URLs, enabling automated bookmarking functionality without requiring the core monitoring system to perform complex content analysis itself.
Solution Approach 2:
The system divides functionality into separate modules: network traffic monitoring handles packet capture and URL extraction, while a separate web crawler handles content indexing and tag association. This segmentation allows each component to specialize in its function, improving overall automation capability while managing system complexity through modular architecture.
2Productivity
If manual bookmarking is used, then users can save and tag URLs, but the system cannot automatically identify popular content without relying on user participation
Solution Approach 1:
The system performs self-service by automatically monitoring network traffic, extracting URLs, and identifying popular content based on access patterns. Instead of relying on users to manually bookmark and tag content, the system autonomously collects usage data and generates bookmark recommendations, thereby preserving valuable usage pattern information that would otherwise be lost.
Solution Approach 2:
The system implements feedback loops where network traffic data is continuously monitored, analyzed, and used to update popularity rankings of URLs. This feedback mechanism enables the system to dynamically adapt to changing user interests and automatically identify emerging popular content, maintaining continuous learning from usage patterns.
3Adaptability or versatility
If traffic monitoring systems are used, then network operations can be performed, but the systems are not used for general purpose social bookmarking
Solution Approach 1:
The patent extends the functionality of traditional traffic monitoring systems by integrating social bookmarking capabilities. The same network monitoring infrastructure is used to automatically collect URL data, while additional components enable content indexing, tag generation, and popularity ranking, creating a multi-functional system that serves both network operations and social bookmarking purposes.
Solution Approach 2:
The system eliminates the need for user interaction by automatically performing bookmark creation, tagging, and organization based on network traffic patterns. Users simply need to be connected to the network, and the system autonomously handles all bookmarking operations, significantly improving ease of operation compared to manual methods.
Data Source
AI summary
A system comprises a packet data processing element; first network resource tracking logic operable to perform monitoring data packets as the packets pass through the network element; detecting network resource identifiers within the data packets; forming network resource identifier report messages that carry the network resource identifiers; forwarding the network resource identifier report messages to a bookmark processing server; storing records of each of the network resource identifiers carried therein; storing counters that identify numbers of times that associated network resource identifiers were requested; determining interesting network resource identifiers based on the records and decision steps; generating and providing a report of the interesting network resource identifiers. As one result, interesting network resource identifiers can be automatically found in network traffic and provided to a social bookmarking site.