Web Domain Ranking with Persistent Connection Detection
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Solution Overview
Problem
Traditional web domain ranking techniques struggle to effectively handle dynamic referral relationships in scale-free networks like the Internet, which are influenced by seasonality, trends, and competitive traffic redirection efforts, leading to challenges in accurately predicting persistent network connections and traffic patterns.
Innovation Solution
A method that maps competitive computer network environments by determining persistence properties of network connections and calculating referral values based on direct and indirect network traffic, as well as potential deleterious effects, to rank source domains that drive traffic to target domains, using a formula that combines direct and propagation values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional web domain ranking techniques are used, then simplicity of implementation is maintained, but accuracy in predicting persistent network connections and traffic patterns deteriorates due to inability to handle dynamic referral relationships
Solution Approach 1:
The patent segments the network connection analysis into persistence detection (identifying stable connections) and dynamic traffic pattern analysis (handling seasonal and competitive variations). This allows the system to focus computational resources on identifying reliable persistent connections while separately modeling dynamic effects, thereby improving prediction accuracy without overwhelming system complexity.
Solution Approach 2:
The system performs preliminary detection of persistent network connections before conducting detailed traffic pattern analysis. By pre-identifying stable referral relationships, the system establishes a foundation of reliable connections that can be used as baseline for predicting future traffic patterns, improving overall prediction accuracy while reducing the complexity of real-time analysis.
2Measurement precision
If dynamic factors such as seasonality and competitive redirection are incorporated, then comprehensiveness of traffic pattern analysis is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by differentiating the analysis approach for different types of network connections. Persistent connections receive simplified modeling focusing on stability, while dynamic connections involving seasonal or competitive factors receive more detailed analysis. This localized approach allows comprehensive coverage of all factors without uniformly applying complex computational methods to every connection type.
Solution Approach 2:
The system implements partial action by focusing computational resources on the most significant dynamic factors affecting traffic patterns, such as major seasonal variations and key competitive redirection efforts. Rather than attempting to model every possible dynamic factor with equal detail, the system identifies and prioritizes the most impactful factors, achieving comprehensive analysis where it matters most while controlling overall computational complexity.
3Measurement precision
If referral values are calculated based on both direct and indirect network traffic, then accuracy of domain ranking is improved, but calculation time increases
Solution Approach 1:
The patent calculates direct referral values first as a preliminary step before computing indirect referral values. By establishing the direct traffic baseline first, the system can then efficiently compute indirect propagation effects based on already-known persistent connection patterns. This sequential approach improves ranking accuracy by incorporating both direct and indirect traffic while reducing total calculation time through efficient ordering of operations.
Solution Approach 2:
The system applies dynamics by implementing iterative calculation methods where indirect referral values are computed based on updated direct value information. The calculation process dynamically adjusts as persistent connection patterns are identified, allowing the system to converge on accurate rankings more efficiently by leveraging previously computed results rather than performing all calculations from scratch.
Data Source
AI summary
A method according to one embodiment includes mapping the competitive computer network environment based on network connections between web domains within the competitive computer network environment, wherein the web domains include at least a target domain and a plurality of source domains, determining persistence properties of the network connections between the web domains to identify network connections that are expected to persist for at least a threshold period of time, determining, for each source domain of the plurality of source domains having a network connection with the target domain expected to persist for at least the threshold period of time, a referral value indicative of an amount of network traffic directed from the source domain to the target domain, and ranking the source domains based on the corresponding referral values.