Proxy Log Analysis for Main Page View Identification
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Solution Overview
Problem
Existing systems for monitoring web content and crediting main page views often inaccurately differentiate between foreground and background requests, leading to distorted monitoring results and requiring constant maintenance due to website changes and embedded traffic.
Innovation Solution
The implementation of a sorting circuitry that analyzes timestamps and application information to identify and credit main page views, discarding embedded traffic and accurately determining page views even through VPN connections, using processor circuitry to access and process request logs and identify main page requests based on response times, data sizes, and status codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems monitor web content using proxy servers or VPN connections, then web activity can be captured, but the systems cannot accurately differentiate between foreground and background requests, leading to distorted monitoring results
Solution Approach 1:
The system segments web requests into foreground requests (user-initiated main page views) and background requests (automated embedded traffic) by analyzing timestamps, application information, and request patterns. This segmentation allows accurate differentiation and prevents background requests from distorting monitoring results.
Solution Approach 2:
The patent introduces an intermediary analysis layer that processes captured web traffic between the proxy server/VPN connection and the monitoring system. This intermediary layer applies algorithms to identify main page requests versus embedded traffic, ensuring accurate measurement without distortion from automated requests.
2Productivity
If systems credit all web requests as main page views, then monitoring coverage is maximized, but false positives from background requests increase
Solution Approach 1:
The system dynamically adjusts crediting decisions based on real-time analysis of request characteristics including timestamps, application information, and patterns. Rather than static crediting rules, the system adapts to distinguish genuine user engagement from automated background traffic, maintaining both coverage and accuracy.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously analyzes crediting results and refines its identification algorithms. By monitoring patterns in credited page views and comparing against known background traffic characteristics, the system improves its ability to avoid false positives while maintaining comprehensive coverage.
3Measurement precision
If systems continuously update monitoring algorithms to adapt to website changes, then measurement accuracy is maintained, but system complexity and maintenance requirements increase
Solution Approach 1:
The system employs self-service mechanisms where algorithms automatically adapt to website changes through pattern recognition and machine learning. Rather than requiring manual updates for each website modification, the system autonomously learns new patterns and adjusts its identification criteria, reducing maintenance complexity while preserving accuracy.
Solution Approach 2:
The patent utilizes parameter changes in request characteristics (timestamps, data sizes, status codes, application information) to identify main page views without requiring structural changes to the monitoring system. By focusing on evolving parameters rather than fixed website structures, the system maintains accuracy through natural adaptation rather than active maintenance.
4Measurement precision
If systems analyze detailed request information to accurately identify main page views, then measurement precision improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis by examining key identifying characteristics (timestamps, application information, request patterns) early in the processing pipeline. By pre-filtering and pre-classifying requests based on these initial indicators, the system reduces the computational burden of detailed analysis while maintaining high accuracy in identifying main page views.
Solution Approach 2:
The patent applies partial analysis to most requests (examining only key identifying parameters) and reserves excessive detailed analysis for borderline cases that require closer inspection. This selective approach processes the majority of requests efficiently while maintaining accuracy for ambiguous cases, optimizing the balance between processing speed and measurement precision.
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture are disclosed to identify main page views. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to: access a log of requests from a proxy, the log of requests including main page requests and embedded page requests, the log of requests including timestamps corresponding to the main page requests and the embedded page requests, identify, based on consecutive ones of the timestamps occurring within a time interval, at least one of the main page requests associated with the time interval, and credit the at least one of the main page requests as a main page view.