Citation Graph Expertise Ranking for Source Trustworthiness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for information retrieval lack the ability to effectively assess the trustworthiness of sources, leading to unreliable decision-making due to the absence of objective measures of influence and reputation, making it difficult to identify credible experts and relevant information.
Innovation Solution
A system and method that utilize a citation graph to compute and rank sources based on their relative expertise, incorporating influence scores to identify experts in real-time, without pre-defined categorization, by analyzing citations across various platforms like social media and web sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional search engines and community boards are used to locate information, then information can be found, but there is no measure of source trustworthiness or influence
Solution Approach 1:
The patent introduces an intermediary system that computes influence scores and expertise metrics, acting as a mediator between information sources and seekers. This intermediary layer processes citation data and generates trustworthiness indicators without altering the original information content.
Solution Approach 2:
The patent replaces subjective human judgment of source reliability with an automated computational system that calculates influence scores based on citation graphs and network analysis, substituting mechanical computation for human evaluation.
2Reliability
If personal recommendations are used, then trusted information can be obtained, but the network of references is limited and subjective
Solution Approach 1:
The patent creates a universal influence scoring system that can evaluate any information source across multiple platforms and domains, replacing limited personal networks with a broadly applicable computational framework that works across diverse contexts.
Solution Approach 2:
The patent adds a new dimension of objective influence measurement to the subjective personal recommendation system, transforming one-dimensional personal trust into multi-dimensional assessment incorporating citation frequency, network position, and expertise metrics.
3Measurement precision
If extensive manual evaluation of source influence is performed, then accurate trustworthiness assessment can be achieved, but the process becomes time consuming
Solution Approach 1:
The patent implements a self-service system where sources automatically generate their own influence scores through computational analysis of their citation networks, eliminating the need for manual evaluation while maintaining high measurement precision through automated algorithms.
Solution Approach 2:
The patent performs preliminary computation of influence scores and expertise metrics in advance, storing these pre-calculated values for rapid retrieval during information seeking, thereby avoiding time-consuming real-time analysis while maintaining assessment accuracy.
4Ease of operation
If subjective value judgments are made about data sources, then personal preferences can be satisfied, but objective comparison between sources is difficult
Solution Approach 1:
The patent transforms subjective qualitative judgments into objective quantitative parameters including influence scores, expertise metrics, and citation counts, enabling precise comparison between sources while preserving ease of use through standardized measurable attributes.
Data Source
AI summary
A new approach is proposed that contemplates systems and methods to provide a ranking of cited objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of “experts” on “topics” without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.