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CN-121981866-A - Intelligent guiding method and system combining AI large model with digital man assistant

CN121981866ACN 121981866 ACN121981866 ACN 121981866ACN-121981866-A

Abstract

The application provides an intelligent guiding method and system combining an AI large model with a digital man assistant. The method comprises the steps of obtaining historical behavior data, preference data and attribute data of a target user, constructing a user portrait, obtaining real-time demand data of the target user, generating an optimal guiding path by combining the user portrait, obtaining service information of the target user, judging compliance and matching service priority, monitoring operation of a preset intelligent guiding platform in a preset time period, extracting effect evaluation data, evaluating operation effect of the preset intelligent guiding platform according to the effect evaluation data, and taking optimization measures, so that intelligent guiding technology combining an AI large model with a digital man assistant is realized.

Inventors

  • CAO WANYU
  • LUO XIANGXIANG

Assignees

  • 广州卓腾科技有限公司

Dates

Publication Date
20260505
Application Date
20260130

Claims (10)

  1. An intelligent guiding method combining an AI large model with a digital man assistant is characterized by comprising the following steps: acquiring historical behavior data, preference data and attribute data of a target user, and constructing a user portrait; acquiring real-time demand data of the target user, and generating an optimal guide path by combining the user portrait; Acquiring service information of the target user, judging compliance and matching service priority; Monitoring the operation of a preset intelligent guide platform in a preset time period, and extracting effect evaluation data; and evaluating the operation effect of the preset intelligent guide platform according to the effect evaluation data, and taking optimization measures.
  2. 2. The intelligent lead method of claim 1, wherein the obtaining historical behavior data, preference data, and attribute data of the target user and constructing the user representation comprises: Acquiring historical behavior data, preference data and attribute data of a target user; the historical behavior data comprise historical handling behavior record data, interactive feedback data and associated business behavior data; the preference data comprises service mode preference data, transacting rhythm preference data and scenerization preference data; The attribute data comprises basic identity attribute data, capability attribute data, compliance attribute data and credit attribute data; and processing through a preset portrait construction model according to the historical behavior data, the preference data and the attribute data to obtain a user portrait.
  3. 3. The intelligent conducting method combining the AI large model with the digital personal assistant according to claim 2, wherein the acquiring the real-time demand data of the target user and generating the optimal conducting path in combination with the user portrait comprises: acquiring real-time demand data of the target user, wherein the real-time demand data comprises business type data, geographic position data and handling time data; And processing the user portrait by a preset path planning algorithm according to the service type data, the geographic position data and the handling time data to obtain an optimal guiding path.
  4. 4. The intelligent guiding method combining AI large model with digital personal assistant according to claim 3, wherein the acquiring the service information of the target user, judging compliance and matching service priority comprises: Acquiring service information of the target user, wherein the service information comprises service element information, material information and associated service data; Carrying out compliance verification according to the business element information, the material information and the related business data to obtain a compliance coefficient; Extracting and processing according to the service information and combining the real-time demand data to obtain service urgency; extracting user grade weight according to the user portrait; and processing according to the business emergency degree, the user grade weight and the compliance coefficient to obtain the service priority.
  5. 5. The intelligent guidance method of claim 4, wherein monitoring operation of a preset intelligent guidance platform for a preset period of time and extracting effect evaluation data comprises: Monitoring operation of a preset intelligent guide platform within a preset time period, and extracting effect evaluation data, including interactive experience data, accurate service data and performance efficiency data; the interactive experience data comprise voice recognition accuracy, semantic understanding accuracy and multi-mode interactive use rate; the accurate service data comprise personalized service recommendation accuracy and user intention recognition accuracy; the performance efficiency data includes a system average response time and a number of concurrent users.
  6. 6. The intelligent guidance method of claim 5, wherein the evaluating the operation effect of the preset intelligent guidance platform based on the effect evaluation data and taking optimization measures comprises: Weighting processing is carried out according to the voice recognition accuracy, the semantic understanding accuracy and the multi-mode interaction utilization rate, and an interaction experience efficiency coefficient is obtained; Weighting processing is carried out according to the personalized service recommendation accuracy and the user intention recognition accuracy, and a service accuracy coefficient is obtained; processing is carried out according to the average response time of the system and the number of concurrent users through a preset performance evaluation model, and a performance efficiency coefficient is obtained; Weighting according to the interactive experience efficiency coefficient, the service precision coefficient and the performance efficiency coefficient to obtain an effect evaluation coefficient; comparing the effect evaluation coefficient with a preset effect evaluation threshold value to obtain a comparison result; evaluating the operation effect of the preset intelligent guide platform according to the comparison result; If the effect evaluation coefficient is smaller than a preset effect evaluation threshold, the operation effect of the preset intelligent guide platform does not reach the standard, and corresponding optimization measures need to be taken.
  7. The intelligent guiding and handling system combining the AI large model and the digital man assistant is characterized by comprising a memory and a processor, wherein the memory comprises a program of an intelligent guiding and handling method combining the AI large model and the digital man assistant, and the program of the intelligent guiding and handling method combining the AI large model and the digital man assistant realizes the following steps when being executed by the processor: acquiring historical behavior data, preference data and attribute data of a target user, and constructing a user portrait; acquiring real-time demand data of the target user, and generating an optimal guide path by combining the user portrait; Acquiring service information of the target user, judging compliance and matching service priority; Monitoring the operation of a preset intelligent guide platform in a preset time period, and extracting effect evaluation data; and evaluating the operation effect of the preset intelligent guide platform according to the effect evaluation data, and taking optimization measures.
  8. 8. The intelligent lead system of claim 7, wherein the acquiring historical behavior data, preference data, and attribute data of the target user and constructing the user representation comprises: Acquiring historical behavior data, preference data and attribute data of a target user; the historical behavior data comprise historical handling behavior record data, interactive feedback data and associated business behavior data; the preference data comprises service mode preference data, transacting rhythm preference data and scenerization preference data; The attribute data comprises basic identity attribute data, capability attribute data, compliance attribute data and credit attribute data; and processing through a preset portrait construction model according to the historical behavior data, the preference data and the attribute data to obtain a user portrait.
  9. 9. The intelligent lead system of claim 8, wherein the acquiring real-time demand data of the target user and generating an optimal lead path in conjunction with the user representation comprises: acquiring real-time demand data of the target user, wherein the real-time demand data comprises business type data, geographic position data and handling time data; And processing the user portrait by a preset path planning algorithm according to the service type data, the geographic position data and the handling time data to obtain an optimal guiding path.
  10. 10. The intelligent lead system of claim 9, wherein the obtaining the business information of the target user, determining compliance and matching service priorities comprises: Acquiring service information of the target user, wherein the service information comprises service element information, material information and associated service data; Carrying out compliance verification according to the business element information, the material information and the related business data to obtain a compliance coefficient; Extracting and processing according to the service information and combining the real-time demand data to obtain service urgency; extracting user grade weight according to the user portrait; and processing according to the business emergency degree, the user grade weight and the compliance coefficient to obtain the service priority.

Description

Intelligent guiding method and system combining AI large model with digital man assistant Technical Field The application relates to the technical field of intelligent guiding and handling, in particular to an intelligent guiding and handling method and system combining an AI large model with a digital man assistant. Background Along with the digital advancement of government service, the defects of the traditional certificate-handling and guiding mode are obvious, the manual guiding and handling efficiency is low, the cost is high, the rule-based intelligent guiding and handling system is lack of flexibility, the personalized requirements of users cannot be precisely matched, the certificate handling process is complicated, the user experience is poor, meanwhile, the certificate handling service scene is complex, different service requirements are different, and the service consistency and the intelligent distribution service priority are required to be rapidly judged. The AI large model has remarkable advantages in the aspects of natural language processing, data analysis and the like, and the digital human technology can realize anthropomorphic interaction, but in the prior art, the AI large model and the digital human technology are combined and applied to intelligent certificate-handling and guiding, and still have blank. In view of the above problems, an effective technical solution is currently needed. Disclosure of Invention The application aims to provide an intelligent guiding and handling method and system combining an AI large model with a digital man assistant, which can realize the intelligent guiding and handling technology combining the AI large model with the digital man assistant by acquiring historical behavior data, preference data and attribute data of a target user, constructing a user portrait, acquiring real-time demand data of the target user, generating an optimal guiding and handling path in combination with the user portrait, acquiring business information of the target user, judging compliance and matching service priority, monitoring the operation of a preset intelligent guiding and handling platform in a preset time period, extracting effect evaluation data, evaluating the operation effect of the preset intelligent guiding and handling platform according to the effect evaluation data, and taking optimization measures. The application also provides an intelligent guiding method combining the AI large model with the digital man assistant, which comprises the following steps: acquiring historical behavior data, preference data and attribute data of a target user, and constructing a user portrait; acquiring real-time demand data of the target user, and generating an optimal guide path by combining the user portrait; Acquiring service information of the target user, judging compliance and matching service priority; Monitoring the operation of a preset intelligent guide platform in a preset time period, and extracting effect evaluation data; and evaluating the operation effect of the preset intelligent guide platform according to the effect evaluation data, and taking optimization measures. Optionally, in the intelligent guiding method of combining the AI big model with the digital personal assistant, the acquiring the historical behavior data, the preference data and the attribute data of the target user and constructing the user portrait includes: Acquiring historical behavior data, preference data and attribute data of a target user; the historical behavior data comprise historical handling behavior record data, interactive feedback data and associated business behavior data; the preference data comprises service mode preference data, transacting rhythm preference data and scenerization preference data; The attribute data comprises basic identity attribute data, capability attribute data, compliance attribute data and credit attribute data; and processing through a preset portrait construction model according to the historical behavior data, the preference data and the attribute data to obtain a user portrait. Optionally, in the intelligent guiding method of combining the AI big model with the digital personal assistant, the acquiring the real-time demand data of the target user and generating the optimal guiding path in combination with the user portrait includes: acquiring real-time demand data of the target user, wherein the real-time demand data comprises business type data, geographic position data and handling time data; And processing the user portrait by a preset path planning algorithm according to the service type data, the geographic position data and the handling time data to obtain an optimal guiding path. Optionally, in the intelligent guiding method of combining the AI large model with the digital personal assistant, the acquiring the service information of the target user, judging the compliance and matching the service priority includes: Acquiring service informa