用于分类的方法、装置、设备和可读介质
By automatically determining the sample classification results through guiding terms and machine learning models, the problem of high cost and low efficiency in the construction of intent classification systems in existing technologies is solved, and an efficient and accurate intent classification system is built, which is suitable for a variety of application scenarios.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JD DIGITS HAIYI INFORMATION TECHNOLOGY CO LTD
- Filing Date
- 2023-11-14
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for constructing intent classification systems require significant manpower and have low efficiency. Traditional clustering algorithms are difficult to align with the business needs of application scenarios, resulting in a large gap between the generated knowledge classification system and actual requirements, making it impossible to efficiently and automatically construct intent classification systems.
By acquiring guide terms from multiple sample spaces, machine learning models are used to automatically determine sample classification results. Combined with clustering algorithms and guide term templates, a fine-grained intent classification system is generated, reducing human intervention.
It enables the construction of a highly efficient intent classification system without human intervention, automatically determines the classification results, improves construction efficiency and accuracy, and adapts to the business needs of different application scenarios.
Smart Images
Figure CN117493571B_ABST