Product Category Determination Using Phrase Relevancy
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Solution Overview
Problem
Conventional methods for determining product category information are often inaccurate and inefficient, particularly when dealing with complex product category information provided by servers.
Innovation Solution
A method and apparatus that involves a server generating phrases from product title information, searching a database for relevancies with product categories in a product category tree, and associating the product with a leaf node based on calculated relevancies, using a cloud computing platform for analysis and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to determine product category information, then the process is simple, but the accuracy and efficiency are poor
Solution Approach 1:
The system pre-calculates and stores relevancy scores between phrases and product categories in a database before actual product classification is needed. This preliminary action allows the classification process to quickly retrieve and use pre-computed relevancy information, improving both accuracy and efficiency without performing complex calculations in real-time
Solution Approach 2:
The patent introduces an intermediary relevancy calculation mechanism that bridges product information and product categories. Instead of directly classifying products, the system uses pre-calculated relevancy scores as an intermediate step, which are stored in the database and used to determine the most appropriate product category, thereby improving accuracy while maintaining efficiency
2Measurement precision
If complex product category information is provided by the server, then more detailed categorization is possible, but it becomes difficult to select proper category
Solution Approach 1:
The system automatically performs category selection by calculating relevancy scores between product phrases and categories, eliminating the need for manual user selection. The server autonomously determines the most appropriate category based on pre-computed relevancy information, making the process both precise and easy to operate
Solution Approach 2:
The patent replaces manual category selection (mechanical process) with automated relevancy-based classification. Instead of relying on users to manually navigate and select categories from complex category structures, the system uses automated calculation and retrieval of relevancy scores to determine the appropriate category, significantly improving ease of operation while maintaining precision
Data Source
AI summary
A user may submit product title information to a server. The server may generate a phrase based on the product title information. The server may then search a database to find relevancies between the phrase and product categories corresponding to multiple nodes in a product category tree. Based on the relevancies, the server may select a node from the multiple nodes. The server may associate the product title information with the node corresponding to a product category when the node is a leaf node of the product category tree.