Company Comparison via Taxonomy Feature Vectors
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Solution Overview
Problem
Current methods lack an efficient way to compare and recommend similar companies based on their product purchasing or selling patterns, which is crucial for business strategies and market analysis.
Innovation Solution
A system and method that utilize a taxonomy tree to classify products hierarchically, match product patterns, assign point values, create feature vectors, and calculate similarity scores between companies, providing recommendations when a similarity threshold is met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If companies manually analyze transaction histories to find similar business patterns, then business insights can be obtained, but the process is time-consuming and inefficient
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computer-based system that uses taxonomy trees, feature vector generation, and similarity scoring algorithms to efficiently compare company purchase patterns without human intervention
Solution Approach 2:
The system transforms unstructured transaction history data into structured feature vectors by mapping products to taxonomy nodes and aggregating purchase frequencies, enabling efficient computational comparison through standardized parameters
2Measurement precision
If detailed product-level analysis is performed to achieve accurate company comparison, then measurement precision improves, but computational complexity increases
Solution Approach 1:
The patent segments the product catalog into a hierarchical taxonomy tree structure, dividing complex product classification into manageable levels (e.g., category, subcategory, specific product) that can be processed and aggregated systematically
Solution Approach 2:
The system merges detailed product-level purchase data into aggregated feature vectors by combining purchase frequencies across multiple taxonomy nodes, reducing data dimensionality while preserving meaningful patterns for comparison
Data Source
AI summary
A method for comparing purchase patterns includes matching multiple products purchased by a base company to multiple leaf nodes in a taxonomy tree to obtain multiple matching leaf nodes. The taxonomy tree is a hierarchical classification of products. The method further includes assigning, to each of the matching leaf nodes and to each parent node of the matching leaf nodes, a point value to obtain multiple point values, creating, for the base company and by a computer processor, a base feature vector including the point values, and calculating, by the computer processor, a similarity score between the base feature vector of the base company to a test feature vector of a test company. The method further includes providing, in response to the similarity score satisfying a similarity threshold, a recommendation.