Intelligent question answering method and device, electronic device, and readable storage medium

By extracting user style and attribute features, and combining multi-turn dialogue coding and intent recognition models, personalized response information is generated, which solves the problem of low user demand matching in existing intelligent question answering methods and achieves a precise interactive experience.

CN122364407APending Publication Date: 2026-07-10BEIJING SUPERHEXA CENTURY TECH CO LTD
View PDF 0 Cites 0 Cited by

Patent Information

Application Number
CN202610663718.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-14
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing intelligent question answering methods fail to effectively combine users' interaction style preferences and objective attribute information, resulting in a low degree of consistency between intent recognition results and users' actual needs, and the generated response content lacks personalization and adaptability.

Method used

By extracting user-defined style description text and attribute information, style feature sets and attribute feature sets are generated. Combined with vectorization and temporal coding of multi-turn dialogues, and using a preset intent recognition model and large language model, personalized response information is generated.

Benefits of technology

It improves the personalization and intent recognition accuracy of intelligent question answering, ensuring that responses closely align with users' core needs and preferences, and providing a precise and personalized interactive experience.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122364407A_ABST
    Figure CN122364407A_ABST
Patent Text Reader

Abstract

This application provides an intelligent question-answering method, device, electronic device, and readable storage medium, belonging to the field of intelligent interaction. The method includes: extracting user-defined style description text to obtain a style feature set; obtaining an attribute feature set based on attribute information; vectorizing historical dialogue sequences and aggregating them through temporal encoding to obtain a context encoding vector; obtaining a candidate intent set and confidence level through a preset intent recognition model; determining the target matching degree by combining style, attribute feature set, context encoding vector, and confidence level, thereby determining the target intent and intent prompt words; and finally generating response information for the current input through a large language model. The intelligent question-answering method, device, electronic device, and readable storage medium provided by this application can provide users with an accurate and personalized interactive experience.
Need to check novelty before this filing date? Find Prior Art