Voice Shopping System Personalizing Search via User History
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Solution Overview
Problem
Existing voice shopping systems lack personalized processing of voice inputs, leading to low recognition efficiency and poor user experience due to reliance on simple internet interconnections without considering user-specific shopping habits.
Innovation Solution
A voice shopping method and device that processes voice inputs based on users' personal shopping habits by determining keywords through semantic recognition, narrowing search ranges using historical shopping data systems, and providing voice outputs for commodity information and ordering instructions, thereby improving recognition efficiency and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If voice shopping systems use simple internet interconnections without personalized processing, then system complexity is reduced, but voice recognition efficiency and user experience deteriorate
Solution Approach 1:
The system pre-stores user shopping behavior records including search history, purchase history, and browsing history in a database before voice recognition occurs. When a voice query is received, the system immediately retrieves relevant pre-stored data to personalize the search scope and results, eliminating the need for complex real-time analysis while maintaining high recognition efficiency and personalized user experience.
2Measurement precision
If the search scope is not narrowed based on user behavior records, then the system can handle diverse queries, but recognition precision and relevance of results worsen
Solution Approach 1:
The system dynamically adjusts the search scope based on the user's shopping behavior records. For example, if a user frequently searches for electronics, the system narrows the default search scope to electronics categories while still allowing the user to browse other categories when needed. This dynamic adaptation maintains high recognition precision for typical queries while preserving versatility for diverse shopping needs.
3Ease of operation
If manual input operations are used for shopping, then system complexity is reduced, but ease of operation and user convenience deteriorate
Solution Approach 1:
The system replaces manual typing and clicking operations with voice-based interaction. Users can search for products, view details, add items to cart, and place orders using natural speech. The voice recognition system converts spoken commands into actionable operations, eliminating the need for physical keyboard or touchscreen input while significantly improving shopping convenience.
Data Source
AI summary
The present disclosure relates to a voice shopping method, device, and a computer-readable storage medium, and relates to the field of voice recognition technology. The method includes: receiving a query instruction from a user by voice, and performing semantic recognition on the query instruction to determine one or more keywords of query content of the user; determining a search range of the keywords according to one or more shopping behavior records of the user; searching the keywords within the search range to obtain commodity information related to the query content, and performing voice output; and receiving an ordering instruction from the user by voice, and performing semantic recognition on the ordering instruction to determine whether an order is made.