AI-Guided Product Search for Bulk Procurement Decisions
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Solution Overview
Problem
Existing product search systems face challenges in providing accurate search results for Class B buyers, who require professional decision factors for bulk procurement or customization, leading to high labor costs and user resentment due to numerous manual configuration requirements.
Innovation Solution
Implement an AI large model to generate and display interactive decision parameters related to bulk procurement or customization, allowing users to set parameter values in multiple rounds of interaction, with the AI model performing inference analysis on product and user behavior data to update search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration of decision parameters is used for bulk procurement search, then professional decision factors can be provided, but labor costs increase and user resentment occurs due to numerous manual configuration requirements
Solution Approach 1:
The system automatically generates and configures professional decision parameters using AI large models, eliminating the need for manual configuration. The AI model autonomously analyzes product information and user behavior data to create relevant parameters, allowing the system to serve itself rather than requiring manual intervention for each search scenario.
Solution Approach 2:
The patent dynamically adjusts decision parameters based on AI inference analysis of product information and user behavior data. Instead of fixed manual configurations, the system transforms and adapts parameters automatically according to the specific search context, product category, and user preferences, enabling flexible and accurate search without manual overhead.
2Ease of operation
If traditional filtering functions are provided for product search, then users can narrow down search scope, but operational difficulties arise due to level-by-level category selection requirements
Solution Approach 1:
The system pre-generates professional decision parameters and their corresponding parameter values using AI large models before users initiate searches. By preparing the filtering options in advance based on product information and user behavior analysis, the system eliminates the need for users to navigate through multiple category levels during the search process, significantly reducing search time and operational complexity.
Solution Approach 2:
The patent introduces AI-generated professional decision parameters as an intermediary layer between user intent and product results. Instead of requiring users to directly navigate category hierarchies, the AI parameters act as a mediator that translates user needs into filtered results, simplifying the interaction and reducing the time users spend on search operations.
3Measurement precision
If AI large model generates professional decision parameters for bulk procurement, then search accuracy improves for Class B buyers, but system complexity increases
Solution Approach 1:
The patent employs a universal AI large model that can generate professional decision parameters across multiple product categories and industries. Rather than implementing separate parameter generation systems for each category, the single AI model performs multiple functions including analyzing product information, understanding user behavior patterns, and creating relevant decision parameters for diverse search scenarios, thereby managing system complexity while maintaining high search accuracy.
Data Source
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AI summary
A product search method including: providing an interactive area in a product search result page after receiving a product search request input by a first user, wherein the interactive area is configured to provide a plurality of decision parameters, some or all of the decision parameters being associated with parameter value alternatives; and the decision parameters displayed in the interactive area comprise: a portion of professional decision parameters related to bulk procurement or customization of products in a category or industry to which a currently searched product belongs; the professional decision parameters are generated by an artificial intelligence AI large model after performing an inference analysis on product information and/or user behavior data in the category or industry; and updating product search results after receiving a parameter value setting result completed by the first user for the plurality of decision parameters.