A method and a system for detecting a dishonest user in an online rating system

Simple SummaryContent extracted from patent full text and abstract with AI.

This invention provides a method and system for detecting and managing dishonest users in online rating systems, such as those used for product, seller, and service reviews. The system uses advanced algorithms to calculate a metric (called an 'honesty estimator') for each rater, based on the distribution of their ratings compared to others. Dishonest raters—those whose rating patterns deviate substantially from the norm—are identified, and rewards for contributing ratings are adjusted accordingly. The system is scalable, using a distributed architecture, and aims to improve the reliability and integrity of online ratings by promoting honest participation and discouraging manipulation.

Use CasesContent extracted from patent full text and abstract with AI.

• Online marketplaces (e.g., Amazon, eBay) to identify and penalize users who submit fake or biased product reviews.
• Auction platforms to prevent manipulation through dishonest buyer or seller ratings.
• Movie or entertainment review websites (e.g., IMDb, Rotten Tomatoes) to filter out extreme or random ratings that distort average scores.
• Service review sites (e.g., Yelp, TripAdvisor) to maintain credibility by identifying rating abuse.
• Price comparison and product information portals to ensure that user-generated content reflects genuine experiences.
• Any online community where user reputation scores are used for transactions, hiring, or collaboration.

BenefitsContent extracted from patent full text and abstract with AI.

• Enhances the trustworthiness and reliability of online rating systems by detecting and penalizing dishonest raters.
• Promotes honest participation by explicitly rewarding users who provide trustworthy ratings.
• Discourages rating manipulation, reciprocal rating schemes, and revenge ratings by reducing the benefits of dishonest behavior.
• Improves overall quality and value of reputation data for buyers, sellers, and community members.
• Highly scalable architecture enables deployment in large, high-traffic systems without performance bottlenecks.
• Flexible threshold settings allow system administrators to tune the strictness of honesty detection according to the needs of the platform.

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Patent Abstract

The present invention relates generally to a method and a system for protecting an online rating system against dishonest users and particularly to a method, a system and a computer-readable medium storing a computer program which allow to detect at least one dishonest rater participating in an online rating system. A distributed system 10 including a master (20) and slave devices (30, 40, 50) is provided which performs a mechanism to detect dishonest raters and halt rewards accordingly as well as to explicitly reward raters who participate in a reputation management system by submitting trustworthy ratings. That mechanism works with users having submitted different numbers of ratings with respect to a plurality of entities.