Referral Tree Construction for Browser History Reconstruction
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Solution Overview
Problem
Current web meter systems cannot accurately reconstruct a user's browser history from recorded URL requests, as they fail to differentiate between sites entered directly and ancillary data, leading to incomplete interaction analysis.
Innovation Solution
A system that employs data segmentation, referral tree construction, enhancement, signal computation, and classification modules to differentiate between user-entered URLs and ancillary data, using HTTP referrer fields, time-based rules, and statistical analysis to reconstruct a user's browser history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a web meter records all URL requests to reconstruct browser history, then the completeness of recorded data is improved, but the ability to differentiate between user-entered URLs and ancillary data deteriorates
Solution Approach 1:
The patent segments the recorded URL requests into different categories by analyzing HTTP referrer fields and applying time-based rules. The system divides URLs into user-entered URLs (direct navigation) and ancillary data (automatically loaded resources), allowing precise differentiation while maintaining complete recording of all requests.
Solution Approach 2:
The patent uses HTTP referrer fields as an intermediary indicator to distinguish between user-entered URLs and ancillary data. By examining the referrer information and applying time-based analysis, the system can identify the origin and purpose of each URL request without losing complete recording capability.
2Measurement precision
If the system analyzes all recorded URL requests to reconstruct browser history, then the accuracy of user interaction analysis is improved, but the computational complexity and processing time worsen
Solution Approach 1:
The patent extracts only the essential information needed for browser history reconstruction by focusing on HTTP referrer fields and time-based patterns. Instead of analyzing all aspects of each URL request, the system selectively extracts key indicators that differentiate user-entered URLs from ancillary data, reducing computational complexity while maintaining accuracy.
Solution Approach 2:
The patent applies time-based rules and preliminary filtering to quickly identify and categorize URL requests before detailed analysis. By pre-processing the data with time-based thresholds and referrer field analysis, the system reduces the computational burden on subsequent processing stages.
Data Source
AI summary
A system for pagination of data based on recorded URL requests, includes a data store comprising a computer readable medium storing a program of instructions for performing the pagination of data based on recorded URL requests; a processor that executes the program of instructions; a data segmentation module to receive a log of the URL requests, and to segment the log for a specific source; a referral tree construction module to construct a referral tree for the specific source based on the segmented log and HTTP referrer fields associated with the log; a tree enhancement module to enhance the referral tree based on site-specific rules; a signal computation module to perform signal computation on a plurality of nodes associated with the enhanced referral tree; a classification module to identify each of the plurality of nodes subsequent to the signal computation is performed on the enhanced referral tree; and a page construction module to construct a web page based on the enhanced referral tree subsequent to the classification module identifying the plurality of nodes.