User-Sensitive PageRank With Personalized Teleportation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional PageRank formulations fail to accurately reflect user behavior and link reliability, leading to unrealistic assumptions and inefficiencies in computing authority weights for Web pages, particularly due to uniform teleportation and link weighting assumptions.
Innovation Solution
The proposed solution involves generating authority values for documents by incorporating user data to weight outbound and inbound links, and estimating teleportation distributions based on user behavior, allowing for more realistic and dynamic PageRank computations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If uniform teleportation is used in PageRank computation, then mathematical requirements are met, but user behavior realism deteriorates
Solution Approach 1:
The patent applies local quality by transitioning from uniform teleportation to personalized teleportation probabilities. Each user is assigned an individual teleportation probability based on their browsing behavior, allowing different parts of the system (different users) to have different properties rather than a single uniform approach. This resolves the contradiction by maintaining mathematical validity while improving user behavior realism through localized customization.
Solution Approach 2:
The patent implements dynamics by making teleportation probabilities adaptive rather than static. The system dynamically adjusts teleportation probabilities based on observed user behavior patterns, allowing the PageRank computation to evolve and reflect actual user interactions. This dynamic approach maintains mathematical requirements while continuously improving accuracy of user behavior representation.
2Ease of manufacture
If uniform link weighting is used, then computational simplicity is maintained, but link reliability accuracy deteriorates
Solution Approach 1:
The patent applies local quality by assigning different weights to different links based on their characteristics and reliability. Instead of uniform weighting, each link receives a personalized weight reflecting its actual importance and trustworthiness. This allows the system to maintain computational efficiency while significantly improving link reliability accuracy through localized differentiation.
Solution Approach 2:
The patent implements parameter changes by introducing weight parameters for different links based on observed user behavior. The system modifies the traditional uniform weight parameter to include link-specific weights that capture variations in link reliability. This parameter refinement maintains computational tractability while substantially improving measurement precision of link quality.
3Productivity
If aggregated PageRank by site is used, then computational efficiency is improved, but ranking precision deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the PageRank computation into user-specific segments rather than aggregating all users into a single computation. Each user's browsing behavior is processed separately to generate personalized teleportation probabilities, then these segmented results are combined. This segmentation maintains computational efficiency through modular processing while improving ranking precision by preserving individual user behavior patterns.
Data Source
AI summary
Techniques are described for generating an authority value of a first one of a plurality of documents. A first component of the authority value is generated with reference to outbound links associated with the first document. The outbound links enable access to a first subset of the plurality of documents. A second component of the authority value is generated with reference to a second subset of the plurality of documents. Each of the second subset of documents represents a potential starting point for a user session. A third component of the authority value is generated representing a likelihood that a user session initiated by any of a population of users will end with the first document. The first, second, and third components of the authority value are combined to generate the authority value. At least one of the first, second, and third components of the authority value is computed with reference to user data relating to at least some of the outbound links and the second subset of documents.