Weighted Vehicle Search Filtering System
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Solution Overview
Problem
Current vehicle filtering systems rely on binary value matching, which can exclude vehicles that are acceptable to users due to inflexible attribute requirements, making it difficult for users to find vehicles with attributes that are considered important but also allow for flexibility in other attributes.
Innovation Solution
A system and method for filtering vehicle information based on conditions and weights in a vehicle search request, where a search query is formed by extracting conditions and weights, applying search query rules, and generating a result set and a partial match set, allowing for vehicles that match specific attributes, are within attribute ranges, and optionally include vehicles with other attributes, enabling users to adjust weights for flexible results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If binary value matching is used for vehicle filtering, then search precision is improved, but adaptability deteriorates
Solution Approach 1:
The patent applies dynamics by transforming static binary matching into dynamic weighted scoring. Vehicle attributes are evaluated on continuous scales with adjustable weights, allowing the system to adapt to different user preferences. The scoring mechanism dynamically adjusts match quality based on multiple attributes rather than using fixed binary thresholds.
Solution Approach 2:
The patent changes parameters by introducing weight values for different attributes and using continuous scoring ranges instead of binary values. This allows flexible adjustment of attribute importance and enables partial matches to be represented numerically, resolving the contradiction between precision and adaptability.
2Reliability
If strict attribute matching is applied, then reliability is improved, but loss of information deteriorates
Solution Approach 1:
The patent applies partial action by implementing partial matching capabilities. Instead of requiring complete attribute matches, the system calculates scores based on partial matches and returns results ordered by match quality. This preserves reliable matching for critical attributes while recovering information about partially matching vehicles that would otherwise be lost.
3Measurement precision
If multiple attributes are required for vehicle search, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The patent applies segmentation by breaking down complex multi-attribute matching into independent weighted components. Each attribute is evaluated separately with its own weight, and scores are aggregated mathematically. This modular approach maintains measurement precision across multiple attributes while simplifying the overall system complexity through standardized processing steps.
Data Source
AI summary
Disclosed are methods, systems, and non-transitory computer-readable medium for filtering vehicle information. For instance, the method may include receiving a vehicle search request from a user device, the vehicle search request including conditions with corresponding weights. The method may also include, in response to receiving the vehicle search request, forming a search query based on the conditions and the weights of the vehicle search request; obtaining vehicle information; filtering the vehicle information based on the search query to obtain a result set and a partial match set; and transmitting a search result message based on the result set and the partial match set to the user device.