Entity Reputation Ranking for Search Systems
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Solution Overview
Problem
Current search systems fail to effectively incorporate and utilize offline reputation in online environments and vice versa, lacking holistic implementations of attribute specificity, portability, entity dependence, weighting by source reputation, reciprocity, and opinion heterogeneity, which limits the accuracy and relevance of search results.
Innovation Solution
An enhanced search system and method based on entity scoring and ranking that utilizes peer-to-peer voting and network analysis to calculate and rank entities' reputations across multiple domains, allowing for the derivation of domain-specific reputations and the clustering of users based on familiarity and agreement, with features like range/scale voting, Condorcet voting, and statistical adjustments to address biases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If search systems use only online user behavior data (page visits, clicks, links) to determine source reputation, then the system is simple to implement, but the measurement precision of source reputation is insufficient and does not reflect real-world quality
Solution Approach 1:
The patent combines online search behavior data with offline reputation data from multiple sources (social media, news outlets, review sites, professional networks) into a unified reputation scoring system. This merging allows the system to capture both digital interactions and real-world entity quality, significantly improving measurement precision while managing complexity through automated data aggregation and standardized scoring algorithms.
Solution Approach 2:
The patent introduces reputation scoring algorithms and data aggregation mechanisms as intermediaries between raw data sources and search results. These intermediaries process, validate, and standardize data from diverse sources (online behavior, social media, news, reviews) into standardized reputation scores, enabling accurate measurement without requiring direct integration of every data source into the search engine core.
2Reliability
If search systems incorporate multiple reputation sources and peer-to-peer voting, then the reputation measurement becomes more accurate and holistic, but the device complexity increases significantly
Solution Approach 1:
The patent segments the reputation assessment system into distinct modular components: data collection modules for different sources (social media, news, reviews, professional networks), processing modules for validating and scoring individual sources, aggregation modules for combining scores, and weighting modules for adjusting influence based on source credibility. This segmentation improves reliability through comprehensive multi-source assessment while managing complexity through independent, reusable modules that can be developed and maintained separately.
Solution Approach 2:
The patent creates a universal reputation scoring framework that can evaluate multiple entity types (individuals, organizations, web pages, products) using the same core algorithms and data sources. This multi-functional approach improves reliability by applying consistent standards across diverse entities while reducing complexity through a single reusable architecture rather than separate systems for each entity type.
3Loss of information
If search systems use aggregated online user behavior data to approximate source quality, then the system is easy to operate, but the information provided is inadequate and search results are less useful
Solution Approach 1:
The patent performs preliminary actions by pre-collecting, validating, and scoring reputation data from multiple sources before search queries are submitted. Reputation scores for entities are calculated and stored in advance based on social media presence, news coverage, review site ratings, professional network endorsements, and historical search behavior. When users submit search queries, the system simply retrieves and applies pre-computed reputation scores, significantly reducing information loss while maintaining ease of operation through cached results and efficient query processing.
Solution Approach 2:
The patent implements self-service mechanisms where entities (individuals, organizations, web pages) can actively manage and update their own reputation data by submitting profiles, links to social media accounts, news articles, review responses, and professional credentials. The system automatically validates and processes these submissions, reducing the operational burden on search system administrators while ensuring comprehensive and up-to-date reputation information is available for accurate search results.
Data Source
AI summary
Enhanced search system and method based on entity ranking that accepts votes for online and offline users and calculates rankings for user attributes that are used to provide highly valued search results. An input is received from a user indicating an opinion of another user or plurality of other users. In one embodiment, reputation scores are weighted by the reputation scores of voters. In another embodiment, weights are derived from voter reputation scores in the domain in which the voting took place. In another embodiment, reputation scores are adjusted according to a plurality of factors, including, but not limited to, user demographics or user behavior.