Graph Database Matching Panelists via Boolean Criteria
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Solution Overview
Problem
Existing market research methods struggle to efficiently match panelists with targeted attributes to projects having low acceptance rates and to reroute panelists who fail to qualify for surveys, leading to suboptimal utilization of resources.
Innovation Solution
A graph database is used to evaluate Boolean expressions and match entities by identifying criteria vertices for panelists, allowing for rapid identification and selection of suitable projects based on profile parameter values, thereby optimizing the matching process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a relational database is used to match panelists to projects, then the matching process can be performed, but the query time is long and resource utilization is suboptimal
Solution Approach 1:
The patent replaces the traditional relational database system with a graph database system. This substitution enables more efficient querying and matching operations by leveraging the graph database's native ability to handle complex relationships and constraints, thereby reducing query time and improving matching efficiency without requiring mechanical optimization of the relational database queries.
Solution Approach 2:
The patent changes the fundamental data structure parameter from relational tables to graph nodes and edges. This parameter change allows the system to represent panelist attributes, project requirements, and matching criteria in a more suitable format that enables faster traversal and evaluation of Boolean expressions, directly addressing the query time and matching efficiency problem.
2Productivity
If panelists are matched to projects with high acceptance rates, then matching is straightforward, but resource utilization is suboptimal
Solution Approach 1:
The patent implements a feedback mechanism where the system evaluates acceptance rates of projects and uses this information to guide the matching process. Panelists are routed to projects based on real-time or historical acceptance rate data, creating a feedback loop that optimizes resource utilization. The graph database queries incorporate these acceptance rate considerations to make intelligent routing decisions.
Solution Approach 2:
The system performs preliminary evaluation of project acceptance rates and panelist qualifications before initiating the matching process. By pre-calculating acceptance rates and pre-filtering compatible projects based on panelist attributes, the system reduces the complexity of the actual matching operation while maximizing resource utilization through informed routing decisions.
3Measurement precision
If complex Boolean expressions are evaluated to match panelist attributes to project criteria, then matching accuracy improves, but query complexity increases
Solution Approach 1:
The patent segments the complex matching problem into distinct components represented as separate graph nodes: panelist nodes with their attributes, project nodes with requirements, criteria nodes with Boolean expressions, and relationship edges. This segmentation allows the graph database to evaluate complex Boolean expressions more efficiently by breaking them down into manageable path queries and node attribute comparisons, maintaining matching accuracy while reducing query complexity.
Data Source
AI summary
A method of matching a first entity to a second entity by evaluating Boolean expressions includes identifying a set of criteria vertices for a second entity vertex by traversing a graph database in a manner constrained to fact vertices identified for the second entity. The graph database relates fact vertices to the criteria vertices by edges corresponding to Boolean expressions for satisfying criteria for matching first entities to second entities. The method additionally includes selecting one of the first entities based on the criteria vertices of the set. The method further includes matching the first entity to the second entity based on the selection.