Large-scale model-driven intelligent training and visual practice system for tax customer service

Abstract

This invention relates to the field of intelligent training technology, specifically to a large-model-driven intelligent training and visual practice system for tax customer service. The system includes a control terminal, a data integration module, an intelligent training generation module, a big data model construction module, a visual practice module, and an early warning module. First, the data integration module integrates multi-dimensional data from customer service personnel. Then, the intelligent training generation module generates personalized training courses for customer service personnel. The big data model construction module constructs a big data model of business scenarios and consultation behaviors. The visual practice module adds a visual interface and compares the content of the visual practice process with the big data model. When the content deviates from the big data model, the early warning module generates an early warning signal. This technical solution provides tax authorities with a comprehensive, systematic, and intelligent training solution.

Description

Technical Field

[0001] This invention relates to the field of intelligent training technology, and in particular to a large-model-driven intelligent training and visual practice system for tax customer service. Background Technology

[0002] In the daily work of the tax bureau, tax customer service personnel play a crucial role. They not only need to master extensive knowledge of tax procedures and policies and regulations, but also need to possess excellent communication skills and problem-solving abilities.

[0003] However, traditional training methods often suffer from problems such as monotonous course content, lack of relevance, and difficulty in real-time updates, resulting in limited improvement in customer service personnel's business capabilities. At the same time, due to the lack of a highly realistic training environment, customer service personnel often lack experience in dealing with complex problems and find it difficult to solve them quickly and accurately. Summary of the Invention

[0004] The purpose of this invention is to provide a large-scale model-driven intelligent training and visual practice system for tax customer service, which solves the problems of traditional training methods, such as monotonous course content, lack of relevance, and difficulty in real-time updates, resulting in limited improvement in the business capabilities of customer service personnel. At the same time, due to the lack of a highly realistic practice environment, customer service personnel often lack experience in dealing with complex problems.

[0005] To achieve the above objectives, the present invention provides a large-model-driven intelligent training and visual practice system for tax customer service. The large-model-driven intelligent training and visual practice system for tax customer service includes a control terminal, a data integration module, an intelligent training generation module, a big data model construction module, a visual practice module, and an early warning module. The control terminal is equipped with the intelligent training generation module, the big data model construction module, the visual practice module, and the early warning module. The data integration module is communicatively connected to the control terminal.

[0006] The data integration module is used to integrate multi-dimensional data on customer service personnel's job functions, skill levels, business knowledge, and past training records.

[0007] The intelligent training generation module is used to generate personalized training courses for customer service personnel based on large model technology.

[0008] The big data model building module integrates historical data and uses big data modeling technology to build big data models of business scenarios and consulting behaviors.

[0009] The visualization training module is based on the intelligent training generation module, with the addition of a visualization interface. It compares the content of the visualization training process with the big data model and uploads the comparison results to the early warning module.

[0010] The early warning module is used to generate an early warning signal when the content during the visualization training process deviates from the big data model, reminding customer service personnel that there is a problem with their current behavior.

[0011] The data integration module includes a data acquisition submodule, a data cleaning submodule, and a data storage submodule. The data acquisition submodule is used to automatically collect multi-dimensional data on customer service personnel's job functions, skill levels, business knowledge, and past training records.

[0012] The data cleaning submodule is used to clean and preprocess the collected data to ensure the accuracy and consistency of the data.

[0013] The data storage submodule is used to store the cleaned data into the database for use by subsequent modules.

[0014] The intelligent training generation module includes a personalized training course generation submodule, an intelligent practice submodule, a real-time knowledge update submodule, and an intelligent training effect evaluation submodule. The personalized training course generation submodule uses multi-dimensional data such as the customer service staff's job functions, skill level, business knowledge mastery, and past training records to tailor personalized training courses for each customer service staff member using a large model algorithm.

[0015] The intelligent training submodule is used to create a highly realistic tax business simulation training environment, simulating various real work scenarios, and allowing users to operate and respond in the simulated environment.

[0016] The real-time knowledge update submodule is used to ensure that the training content is always consistent with the latest tax policies and regulations.

[0017] The intelligent training effectiveness evaluation submodule is used to monitor and evaluate customer service learning performance in real time during the training process and generate a detailed training effectiveness evaluation report.

[0018] The big data model building module includes a historical data collection submodule, a data preprocessing submodule, and a model building submodule. The historical data collection submodule is used to integrate multi-source data such as taxpayer consultation data, service quality data, and business processing data from the call system and the tax collection and payment interaction business system.

[0019] The data preprocessing submodule is used to perform preprocessing operations such as cleaning, deduplication, and normalization on the collected multi-source data.

[0020] The model building submodule uses preprocessed data and big data modeling techniques to construct big data models of tax business scenarios and taxpayer consultation behavior.

[0021] The big data model constructed by the model construction submodule includes consultation volume, consultation hotspots, and consultation trends for different business types.

[0022] The visualization training module includes a visualization training sub-module and a big data model comparison sub-module. The visualization training sub-module adds a visualization interface to the intelligent training sub-module to display the customer service's operation and response in the simulated environment in real time, as well as the system's feedback and evaluation.

[0023] The big data model comparison submodule is used to compare the content of the visualization training process with the big data model to analyze whether the customer service operation is consistent with the tax business scenario and the taxpayer's consultation behavior pattern.

[0024] The early warning module includes an alert submodule and a correction submodule. The alert submodule is used to generate an early warning signal when the content deviates from the big data model during the visualization training process.

[0025] The correction submodule provides customer service with suggestions for improving the current behavior based on the current warning signal.

[0026] This invention discloses a large-scale model-driven intelligent training and visual practice system for tax customer service, comprising a control terminal, a data integration module, an intelligent training generation module, a big data model construction module, a visual practice module, and an early warning module. First, the data integration module integrates multi-dimensional data on customer service personnel's job functions, skill levels, business knowledge, and past training records. Then, the intelligent training generation module generates personalized training courses for customer service personnel. Furthermore, the big data model construction module integrates historical data and uses large-scale model technology to construct a big data model of business scenarios and consultation behaviors. Based on the intelligent training generation module, the visual practice module adds a visual interface and compares the content of the visual practice process with the big data model. When the content of the visual practice process deviates from the big data model, the early warning module generates an early warning signal to alert customer service personnel to problems in their current behavior. This technical solution provides tax authorities with a comprehensive, systematic, and intelligent training solution. Through the application of this system, tax authorities can more effectively improve the business capabilities and service quality of tax customer service personnel, thereby increasing overall work efficiency and taxpayer satisfaction. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of the principle of the large-model-driven intelligent training and visual practice system for tax customer service provided by the present invention.

[0029] Figure 2 This is a partial block diagram of the principle of the large-model-driven intelligent training and visual practice system for tax customer service provided by this invention.

[0030] 101. Control Terminal; 102. Data Integration Module; 103. Intelligent Training Generation Module; 104. Big Data Model Building Module; 105. Visualized Practice Module; 106. Early Warning Module; 107. Data Acquisition Submodule; 108. Data Cleaning Submodule; 109. Data Storage Submodule; 110. Personalized Training Course Generation Submodule; 111. Intelligent Practice Submodule; 112. Real-time Knowledge Update Submodule; 113. Intelligent Training Effectiveness Evaluation Submodule; 114. Historical Data Acquisition Submodule; 115. Data Preprocessing Submodule; 116. Model Building Submodule; 117. Visualized Practice Submodule; 118. Big Data Model Comparison Submodule; 119. Warning Submodule; 120. Correction Submodule. Detailed Implementation

[0031] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0032] Please see Figure 1 and Figure 2 This invention provides a large-scale model-driven intelligent training and visual practice system for tax customer service. The large-scale model-driven intelligent training and visual practice system for tax customer service includes a control terminal 101, a data integration module 102, an intelligent training generation module 103, a big data model construction module 104, a visual practice module 105, and an early warning module 106. The control terminal 101 is equipped with the intelligent training generation module 103, the big data model construction module 104, the visual practice module 105, and the early warning module 106. The data integration module 102 is communicatively connected to the control terminal 101.

[0033] The data integration module 102 is used to integrate multi-dimensional data on customer service personnel’s job functions, skill levels, business knowledge, and past training records.

[0034] The intelligent training generation module 103 is used to generate personalized training courses for customer service personnel based on large model technology.

[0035] The big data model building module 104 integrates historical data and uses big data model technology to build big data models of business scenarios and consulting behaviors.

[0036] The visualization training module 105 is based on the intelligent training generation module 103, with the addition of a visualization interface. It compares the content of the visualization training process with the big data model and uploads the comparison results to the early warning module 106.

[0037] The early warning module 106 is used to generate an early warning signal when the content during the visualization training process deviates from the big data model, reminding customer service personnel that there is a problem with their current behavior.

[0038] In this embodiment, firstly, the data integration module 102 integrates multi-dimensional data on customer service personnel's job functions, skill levels, business knowledge, and past training records. Then, the intelligent training generation module 103 generates personalized training courses for customer service personnel. Furthermore, the big data model building module 104 integrates historical data and uses big data modeling technology to construct a big data model of business scenarios and consultation behaviors. Based on the intelligent training generation module 103, the visualization practice module 105 adds a visualization interface and compares the content of the visualization practice process with the big data model. When the content of the visualization practice process deviates from the big data model, the early warning module 106 generates an early warning signal to remind customer service personnel that their current behavior is problematic. This technical solution provides tax authorities with a comprehensive, systematic, and intelligent training solution. Through the application of this system, tax authorities can more effectively improve the business capabilities and service quality of tax customer service personnel, thereby improving overall work efficiency and taxpayer satisfaction.

[0039] Furthermore, the data integration module 102 includes a data acquisition submodule 107, a data cleaning submodule 108, and a data storage submodule 109. The data acquisition submodule 107 is used to automatically collect multi-dimensional data on customer service personnel’s job functions, skill levels, business knowledge mastery, and past training records from multiple systems such as the tax authority’s call system and tax collection and payment interaction business system.

[0040] The data cleaning submodule 108 is used to clean and preprocess the collected data to ensure the accuracy and consistency of the data;

[0041] The data storage submodule 109 is used to store the cleaned data into a database for use by subsequent modules.

[0042] Furthermore, the intelligent training generation module 103 includes a personalized training course generation submodule 110, an intelligent practice submodule 111, a real-time knowledge update submodule 112, and an intelligent training effect evaluation submodule 113. The personalized training course generation submodule 110 uses multi-dimensional data such as the customer service staff's job functions, skill level, business knowledge mastery, and past training records to tailor personalized training courses for each customer service staff member using a large model algorithm.

[0043] The intelligent training submodule 111 is used to create a highly realistic tax business simulation training environment, simulating various real work scenarios, such as tax declaration review, tax inspection, taxpayer consultation and answering, etc., and to operate and respond in the simulation environment;

[0044] The real-time knowledge update submodule 112 is connected to the tax laws and regulations policy database in real time to ensure that the training content is always consistent with the latest tax laws and regulations. Once there are policy and regulations updates or business process adjustments, the system will immediately and automatically update the training courses and push notifications and learning reminders to relevant customer service.

[0045] The intelligent training effectiveness evaluation submodule 113 uses technologies such as speech recognition, semantic understanding, and behavior analysis to monitor and evaluate customer service learning performance in real time during the training process, and generate a detailed training effectiveness evaluation report.

[0046] Furthermore, the big data model building module 104 includes a historical data collection submodule 114, a data preprocessing submodule 115, and a model building submodule 116. The historical data collection submodule 114 is used to integrate multi-source data such as taxpayer consultation data, service quality data, and business processing data from the call system and the tax collection and payment interaction business system.

[0047] The data preprocessing submodule 115 is used to perform preprocessing operations such as cleaning, deduplication, and normalization on the collected multi-source data.

[0048] The model building submodule 116 uses big data technology to build a big data model of tax business scenarios and taxpayers' consultation behavior based on the preprocessed data.

[0049] The big data model constructed by the model construction submodule 116 includes consultation volume, consultation hotspots, and consultation trends for different business types.

[0050] Furthermore, the visualization training module 105 includes a visualization training sub-module 117 and a big data model comparison sub-module 118. The visualization training sub-module 117 adds a visualization interface on the basis of the intelligent training sub-module 111 to display the customer service's operation and response in the simulation environment in real time, as well as the system's feedback and evaluation.

[0051] The big data model comparison submodule 118 is used to compare the content of the visualization training process with the big data model to analyze whether the customer service operation is consistent with the tax business scenario and the taxpayer's consultation behavior pattern.

[0052] Furthermore, the early warning module 106 includes an alert submodule 119 and a correction submodule 120. The alert submodule 119 is used to generate an early warning signal when the content deviates from the big data model during the visualization training process.

[0053] The correction submodule 120 provides customer service with suggestions for improving the current behavior based on the current warning signal.

[0054] The above description discloses only one preferred embodiment of the present invention, and should not be construed as limiting the scope of the present invention. Those skilled in the art will understand that all or part of the processes of the above embodiments can be implemented, and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A large-model-driven intelligent training and visual practice system for tax customer service, characterized in that, It includes a control terminal, a data integration module, an intelligent training generation module, a big data model construction module, a visual training module, and an early warning module. The control terminal is equipped with the intelligent training generation module, the big data model construction module, the visual training module, and the early warning module. The data integration module is communicatively connected to the control terminal. The data integration module is used to integrate multi-dimensional data on customer service personnel's job functions, skill levels, business knowledge, and past training records. The intelligent training generation module is used to generate personalized training courses for customer service personnel based on large model technology. The big data model building module integrates historical data and uses big data modeling technology to build big data models of business scenarios and consulting behaviors. The visualization training module is based on the intelligent training generation module, with the addition of a visualization interface. It compares the content of the visualization training process with the big data model and uploads the comparison results to the early warning module. The early warning module is used to generate an early warning signal when the content during the visual training process deviates from the big data model, reminding customer service personnel that there is a problem with their current behavior; The intelligent training generation module includes a personalized training course generation submodule, an intelligent practice submodule, a real-time knowledge update submodule, and an intelligent training effect evaluation submodule. The personalized training course generation submodule uses multi-dimensional data such as the customer service staff's job functions, skill level, business knowledge mastery, and past training records to tailor personalized training courses for each customer service staff member using a large model algorithm. The intelligent training submodule is used to create a highly realistic tax business simulation training environment, simulating various real work scenarios, and allowing users to operate and respond in the simulated environment. The real-time knowledge update submodule is used to ensure that the training content is always consistent with the latest tax policies and regulations. The intelligent training effectiveness evaluation submodule is used to monitor and evaluate customer service learning performance in real time during the training process and generate a detailed training effectiveness evaluation report. The big data model building module includes a historical data collection submodule, a data preprocessing submodule, and a model building submodule. The historical data collection submodule is used to integrate multi-source data such as taxpayer consultation data, service quality data, and business processing data from the call system and the tax collection and payment interaction business system. The data preprocessing submodule is used to perform preprocessing operations such as cleaning, deduplication, and normalization on the collected multi-source data. The model building submodule uses preprocessed data and big data modeling techniques to construct big data models of tax business scenarios and taxpayer consultation behavior.

2. The large-model-driven intelligent training and visual practice system for tax customer service as described in claim 1, characterized in that, The data integration module includes a data acquisition submodule, a data cleaning submodule, and a data storage submodule. The data acquisition submodule is used to automatically collect multi-dimensional data on customer service personnel's job functions, skill levels, business knowledge, and past training records. The data cleaning submodule is used to clean and preprocess the collected data to ensure the accuracy and consistency of the data. The data storage submodule is used to store the cleaned data into the database for use by subsequent modules.

3. The large-model-driven intelligent training and visual practice system for tax customer service as described in claim 2, characterized in that, The big data model built by the model building submodule includes consultation volume, consultation hotspots, and consultation trends for different business types.

4. The large-model-driven intelligent training and visual practice system for tax customer service as described in claim 3, characterized in that, The visualization training module includes a visualization training sub-module and a big data model comparison sub-module. The visualization training sub-module adds a visualization interface to the intelligent training sub-module to display the customer service's operation and response in the simulated environment in real time, as well as the system's feedback and evaluation. The big data model comparison submodule is used to compare the content of the visualization training process with the big data model to analyze whether the customer service operation is consistent with the tax business scenario and the taxpayer's consultation behavior pattern.

5. The large-model-driven intelligent training and visual practice system for tax customer service as described in claim 4, characterized in that, The early warning module includes an alert submodule and a correction submodule. The alert submodule is used to generate an early warning signal when the content deviates from the big data model during the visualization training process. The correction submodule provides customer service with suggestions for improving the current behavior based on the current warning signal.

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