AI-Driven Commodity Search Result Grouping and Recommendation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional commodity search systems face low browsing efficiency due to the lack of guided shopping information on search result pages, where users rely solely on images and titles to select commodities, leading to disorganized and non-informative search results.
Innovation Solution
A method utilizing AI large-scale parametric models to analyze user search intent from natural language inputs, generate text content for commodity object combinations, and provide guided shopping information on search result pages, including recommendation reasons and interactive dialogue to refine search results based on user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple commodity information cards are arranged and displayed in the form of information flow, then the search result page can show various commodities, but the browsing efficiency is very low because users rely entirely on their interest in displayed images and titles to decide whether to click
Solution Approach 1:
The patent segments commodity information into organized groups based on categories, prices, and other attributes. Instead of displaying commodities as a flat information flow, the system divides them into structured groups with clear headings and classification, making it easier for users to locate relevant information quickly without browsing through all items individually.
Solution Approach 2:
The patent changes the display parameters by introducing structured organization dimensions such as category, price range, and sales volume. This transforms the presentation from a simple list to a multi-dimensional organized structure, enabling users to filter and identify relevant commodities more efficiently based on their specific needs.
2Ease of operation
If traditional search result pages display only basic commodity information without guided shopping information, then the page layout is simple, but users cannot efficiently find commodities meeting their needs
Solution Approach 1:
The patent introduces an intermediary information layer that mediates between the commodity data and the user's decision-making process. This intermediary layer provides organized grouping information, category labels, and structured presentation that guides users through the selection process, reducing the information gap and making commodity selection more efficient.
Solution Approach 2:
The patent performs preliminary organization and classification of commodity information before presentation to users. By pre-grouping commodities according to relevant attributes and preparing structured display formats in advance, the system reduces the cognitive load on users during browsing, enabling faster and more efficient commodity selection.
Data Source
AI summary
A method comprising determining a plurality of commodity objects meeting a search intent according to a commodity object search request submitted by a user; analyzing the plurality of commodity objects to obtain a plurality of commodity object combinations, and generating text content in units of commodity object combinations, wherein the text content is used for showing recommendation reason information corresponding to the commodity object combinations; and providing, to a client, the commodity object combinations and the corresponding text content to be displayed in a commodity search result page of the client. According to the present disclosure, information displayed on the commodity search result page can guide shopping, thus improving the browsing efficiency of users.