Reputation Score Ranking for Search Query Reliability
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Solution Overview
Problem
Current search systems lack the ability to effectively leverage reputation and influence scores to filter and rank information, leading to unreliable decision-making due to the subjective nature of reputation and the absence of objective measures for trustworthiness in electronic data sources.
Innovation Solution
A system and method that utilize reputation and influence scores to rank entities by determining citation scores based on matching search terms and combining them with reputation scores, allowing for the selection and ranking of objects in search queries, which provides an objective measure of trustworthiness and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional search engines and electronic data sources are used to locate information, then information availability increases, but trustworthiness and reliability of the information decrease
Solution Approach 1:
The patent introduces reputation scores and influence scores as intermediary metrics that mediate between the quantity of information available and the trustworthiness of that information. These scores act as objective indicators that bridge the gap between raw data volume and reliable information, allowing users to assess trustworthiness without manually evaluating each source.
Solution Approach 2:
The patent transforms subjective reputation assessments into objective numerical parameters (reputation scores and influence scores). By converting qualitative trust evaluations into quantitative metrics, the system enables automated ranking and filtering of information sources, thereby improving reliability while maintaining information availability.
2Reliability
If subjective reputation measures are used to evaluate data sources, then personal trustworthiness can be assessed, but objective measurement and consistency across different users are lost
Solution Approach 1:
The patent replaces subjective human judgment mechanisms with automated computational scoring systems. Instead of relying on individual users' subjective reputation assessments, the system uses algorithms to calculate objective reputation scores and influence scores, thereby eliminating variability and ensuring consistent, precise measurements across all users.
Solution Approach 2:
The patent converts subjective reputation concepts into precise quantitative parameters. By defining reputation and influence as measurable numerical scores derived from objective data (such as citation counts, link analysis, and user behavior patterns), the system achieves both personalization and objectivity simultaneously.
3Reliability
If users manually evaluate and make value judgments about data source reputation, then decision-making can be informed by personal experience, but time consumption and effort increase
Solution Approach 1:
The patent performs preliminary computation of reputation scores and influence scores for data sources before users need to evaluate them. By pre-calculating these metrics and storing them in databases, the system eliminates the need for users to perform time-consuming manual evaluations, while still providing high-quality, experience-based reliability assessments.
Solution Approach 2:
The system enables self-service by automatically providing users with pre-computed reputation and influence scores that they can directly use for decision-making. Users don't need to manually evaluate source reliability; the system serves them by providing ready-to-use objective metrics that reflect personal trustworthiness assessments.
4Productivity
If limited information from non-attributed sources is used, then decision-making can proceed with available data, but prediction accuracy and satisfaction decrease
Solution Approach 1:
The patent introduces reputation scores and influence scores as intermediary indicators that enable users to quickly assess the quality of limited information sources. These scores act as mediating metrics that allow rapid decision-making while maintaining high prediction accuracy, bridging the gap between speed and precision.
Solution Approach 2:
The patent transforms limited unstructured information into structured quantitative parameters (reputation and influence scores). By converting scarce data into measurable metrics, the system enables both rapid decision-making and accurate predictions, as the scores provide immediate, objective indicators of information quality.
Data Source
AI summary
One or more processors determine reputation scores for one or more subjects based on connections. One or more processors use a plurality of citations, with each citation representing an expression of opinion or description by a subject on an object. One or more processors select a subset of citations for each object from the citations citing each object. The content of the citations matches one or more search terms for a search query. One or more processors assign citation scores to a subset of a plurality of objects. The citation scores indicate relevance of the objects cited by citations and are determined based at least in part on matching one or more search terms with the content of the citations of the objects by the one or more subjects. The selection scores for an object are determined for each search query based on a subset of subjects citing the object.