Entity Relationship Description via Uniqueness-Based Commonality Filtering
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Solution Overview
Problem
Current internet search engines lack the ability to effectively identify and present interesting common features between different entities, such as businesses, which limits user interaction and the quality of information provided.
Innovation Solution
The method involves identifying related entities based on commonalities, sorting these commonalities by uniqueness, and selecting those above a certain threshold for display, using a system that calculates similarity scores and weights categories based on user interactions and trusted sources to provide descriptive relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If search engines present all common features between entities, then completeness of information is improved, but information quality and user interest are worsened due to inclusion of trivial commonalities
Solution Approach 1:
The patent extracts and presents only the most interesting and unique common features between entities, filtering out trivial commonalities. The system calculates uniqueness scores for each common feature and selectively extracts those above a threshold, thereby presenting a refined subset that maximizes information quality while maintaining relevance.
Solution Approach 2:
The patent introduces a uniqueness parameter to evaluate and rank common features. By changing the selection criterion from mere presence to uniqueness-based ranking, the system transforms the information presentation from comprehensive but noisy to selective and high-quality.
2Speed
If search engines use simple similarity metrics, then processing speed is improved, but accuracy in identifying interesting relationships is worsened
Solution Approach 1:
The patent replaces simple mechanical similarity counting with a uniqueness-based scoring mechanism. Instead of merely counting common features, the system calculates how unique each common feature is across the corpus, providing a more precise measurement of relationship interest while maintaining computational efficiency through scalable algorithms.
3Loss of information
If search engines present detailed relationship descriptions, then information quality is improved, but system complexity is worsened
Solution Approach 1:
The patent segments the relationship description task into distinct components: identifying common features, calculating uniqueness scores, ranking features, and selecting top candidates. This segmentation allows each component to be handled by specialized algorithms, managing system complexity while delivering high-quality relationship descriptions.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating descriptions of relationships between entities. In one aspect, a method includes identifying one or more related entities for a particular entity based at least in part on commonalities between the particular entity and the one or more related entities, sorting the commonalities according to a measure of uniqueness of each of the commonalities, and identifying a subset of the commonalities having a measure of uniqueness above a lower measure of uniqueness threshold. The identified subset of commonalities can include one or more commonalities. One or more commonalities can be selected from the subset of commonalities as indicative of a relationship to the particular entity, and a description of the relationship can be identified based on the selected one or more commonalities.