User Reputation System for Content Quality Filtering
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Solution Overview
Problem
The challenge lies in effectively managing and assessing user-supplied content on the internet, where relevance, accuracy, and quality are often compromised due to the abundance of information, with existing systems struggling to identify and rank content timely and accurately, especially with the rise of user-generated content from various sources like blogs and Web merchants.
Innovation Solution
The implementation of automatically assessed levels of trust for users, based on their prior activities and reputation scores, to evaluate and prioritize content, where higher-trust users' evaluations are given more weight, and content from low-trust users may be suppressed or discounted, ensuring the quality and relevance of content presented to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If volunteer users are solicited to prepare and supply content such as item reviews or images, then cost is reduced and appeal to some readers is improved, but content quality deteriorates with poor writing, poor image quality, irrelevant subject matter, and opinions that differ greatly from most other users
Solution Approach 1:
The patent introduces a reputation system as an intermediary mechanism that mediates between volunteer content creators and the platform. This system assigns reputation scores to users based on their contribution quality, and these scores are used to weight and filter content automatically. The reputation system acts as a mediator that enables the platform to utilize volunteer content while maintaining quality standards through automated reputation-based filtering and weighting.
2Adaptability or versatility
If the number of available sources of content grows with numerous user-generated blogs and blurbs, then content variety increases, but the ability to timely identify and analyze such content deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing reputation scores for users before their content needs to be evaluated. When new content is generated, the system can immediately retrieve the author's pre-computed reputation score and use it for rapid content weighting and filtering. This preliminary preparation of user trust metrics enables fast content identification and analysis without compromising content variety.
3Ease of operation
If search engine techniques are used to locate and rank content by relevance, then content organization is improved, but the difficulty in initially identifying potentially relevant content remains
Solution Approach 1:
The patent adds another dimension to content evaluation by introducing reputation-based weighting as an additional criterion beyond traditional relevance ranking. Instead of solely organizing content by keyword matching and relevance, the system incorporates a second dimension of user reputation scores. This multi-dimensional approach allows the system to maintain relevance-based organization while simultaneously addressing content identification difficulty through reputation-filtered results.
Data Source
AI summary
Techniques are described for managing content by identifying content that has attributes of interest (e.g., content that is useful, humorous and/or that otherwise has a sufficiently high degree of quality) and by determining how to use such identified content. In some situations, a piece of content is automatically assessed in a manner based on automatically assessed levels of trust in users who are associated with the content, such as a user who authored or otherwise supplied the content and/or users who evaluated the content. For example, an automatically assessed level of trust for a user may be based on prior activities of the user and be used to predict future behavior of the user as a supplier of acceptable content and/or as an acceptable evaluator of supplied content, such as based on prior activities of the user that are not related to supplying and/or evaluating content.