Artificial intelligence AI customer service reply system based on cloud service

Abstract

The invention discloses an artificial intelligence AI customer service reply system based on cloud service, which comprises a request receiving module, an instruction processing module, a user feedback module, a background extension module and a record storage module, and is characterized in that the request receiving module is in control connection with an information transmission module; according to the invention, the text synthesis module, the voice synthesis module and the multimedia integration module select texts, voice forms, pictures and links as supplementary instructions according to the preferences of the user, customization can be carried out according to the preferences of the user, and the user experience can be improved; statistical analysis is carried out on the data in the data analysis module, a result is obtained according to information of a statistical chart in the result obtaining module, and a product or service is upgraded according to the obtained result in the continuous upgrading module, so that improvement of the product and the service is facilitated; and when the traffic is increased in the automatic expansion module, the cloud service platform can automatically add the computing resources according to the preset rule, so that the service quality is ensured, and the traffic peak can be dealt with.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent reply systems, and particularly to an artificial intelligence (AI) customer service reply system based on cloud services. Background Art

[0002] Artificial intelligence customer service reply systems can enhance the customer service experience and improve operational efficiency, significantly saving costs and promoting technological upgrades; artificial intelligence customer service reply systems can work continuously, without time restrictions, providing round-the-clock support for users to ensure that help is always available; compared with human customer service, artificial intelligence customer service reply systems can process and respond to user inquiries almost instantaneously, reducing waiting times and providing a smoother user experience; in the long run, deploying an artificial intelligence customer service reply system can significantly reduce labor costs because it reduces the need for a large number of human customer service representatives while also efficiently handling a large number of concurrent requests; the information and services provided by artificial intelligence customer service reply systems are consistent and not affected by emotions or fatigue, thus ensuring high accuracy and reliability; however, the currently popular artificial intelligence customer service reply systems have obvious defects: firstly, they cannot summarize previous data to continuously improve the product and service; secondly, the answers provided are single and cannot be customized according to the needs of customers; finally, they lack the ability to handle peak traffic; therefore, it is necessary to design an artificial intelligence (AI) customer service reply system based on cloud services. Summary of the Invention

[0003] The purpose of the present invention is to provide an artificial intelligence (AI) customer service reply system based on cloud services to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: an artificial intelligence (AI) customer service reply system based on cloud services, including a request receiving module, an information transmission module, a central processing module, a data storage module, an instruction processing module, a user feedback module, a background expansion module, and a record saving module. The request receiving module is controllably connected to the information transmission module, the information transmission module is controllably connected to the central processing module, and the central processing module is respectively controllably connected to the data storage module, the instruction processing module, the user feedback module, the background expansion module, and the record saving module. The user feedback module and the record saving module are controllably connected to the data storage module.

[0005] As a further technical solution of the present invention, the request receiving module is composed of an information receiving module, a data cleaning module, a data integration module, and an information output module. The information receiving module is controllably connected to the data cleaning module, the data cleaning module is controllably connected to the data integration module, and the data integration module is controllably connected to the information output module.

[0006] As a further technical solution of the present invention, the central processing module is composed of a data receiving module, an entity extraction module, a picture extraction module, a text extraction module, an intention recognition module, a dialogue state tracking module, a policy selection module, and a data query module. The data receiving module is controllably connected to the entity extraction module, and the entity extraction module is respectively controllably connected to the picture extraction module and the text extraction module.

[0007] As a further technical solution of the present invention, the picture extraction module and the text extraction module are controllably connected to the intention recognition module, the intention recognition module is controllably connected to the dialogue state tracking module, the dialogue state tracking module is controllably connected to the policy selection module, and the policy selection module is controllably connected to the data query module.

[0008] As a further technical solution of the present invention, the data storage module is composed of a data calling module, a data analysis module, a result obtaining module, and a continuous upgrade module. The data calling module is controllably connected to the data analysis module, the data analysis module is controllably connected to the result obtaining module, and the result obtaining module is controllably connected to the continuous upgrade module.

[0009] As a further technical solution of the present invention, the instruction processing module is composed of a personalized customization module, a response generation module, a text synthesis module, a voice synthesis module, and a multimedia integration module. The personalized customization module is controllably connected to the response generation module, and the response generation module is controllably connected to the text synthesis module.

[0010] As a further technical solution of the present invention, the response generation module is respectively controllably connected to the voice synthesis module and the multimedia integration module.

[0011] As a further technical solution of the present invention, the user feedback module is composed of a feedback receiving module, a user feedback analysis module, and a continuous learning module. The feedback receiving module is controllably connected to the user feedback analysis module, and the user feedback analysis module is controllably connected to the continuous learning module.

[0012] As a further technical solution of the present invention, the background expansion module is composed of an asynchronous task processing module and an automatic expansion module. The asynchronous task processing module is controllably connected to the automatic expansion module.

[0013] As a further technical solution of the present invention, the record saving module is composed of a data log saving module and a real-time monitoring module. The data log saving module is controllably connected to the real-time monitoring module.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: For an artificial intelligence AI customer service reply system based on cloud services, the information receiving module in the request receiving module receives user information through channels such as website chat boxes, mobile applications, and social media. The data is preprocessed in the data cleaning module and the data integration module, and the preprocessed information is output in the information output module and transmitted to the data receiving module in the central processing module through the information transmission module. The entity extraction module, the picture extraction module, and the text extraction module respectively extract the information of pictures and texts. In the intention recognition module, NLP technology is used to parse the user's input to determine the user's intention or request type. In the dialogue state tracking module, the state of the current dialogue is maintained to ensure context consistency in complex interactions. In the strategy selection module, corresponding strategies are selected according to the current situation. In the data query module, the stored product content or training results are called. In the personalized customization module in the instruction processing module, the reply content is adjusted according to factors such as the user's preferences and historical records to provide a personalized service experience. In the response generation module, the system's answer is converted into a natural and fluent language expression. In the text synthesis module, the voice synthesis module, and the multimedia integration module, according to the user's preferences, content in the form of text, voice, or pictures, links, or other forms is selected as supplementary explanations, which can be customized according to the user's preferences and can improve the user experience. In the feedback receiving module of the user feedback module, the evaluation of the user for this service is received. In the user feedback analysis module, the level of the user's evaluation of a certain problem is analyzed. In the continuous learning module, machine learning algorithms are used to continuously optimize the model performance to adapt to new language patterns and changes in user needs. In the data log saving module of the record saving module, all interaction records are recorded for subsequent analysis, troubleshooting, and compliance review. In the real-time monitoring module, an alarm mechanism is set to monitor the health status of the system and the compliance with the service level agreement. In the data call module of the data storage module, the user request data within a certain time is retrieved. In the data analysis module, statistical analysis is performed on the data. In the result obtaining module, results are obtained according to the information in the statistical chart. In the continuous upgrade module, the product or service is upgraded according to the obtained results, which is beneficial to the improvement of the product and service. In the asynchronous task processing module of the background expansion module, for complex queries or long-running tasks, they can be placed in the background queue for asynchronous execution. In the automatic expansion module, when the traffic increases, the cloud service platform can automatically add computing resources according to preset rules to ensure service quality and is beneficial to coping with traffic peaks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is the system flow chart of the present invention;

[0016] Figure 2 It is the schematic structural diagram of the request receiving module in the present invention;

[0017] Figure 3 It is a schematic diagram of the architecture of the central processing module in the present invention;

[0018] Figure 4 It is a schematic diagram of the architecture of the data storage module in the present invention;

[0019] Figure 5 It is a schematic diagram of the architecture of the instruction processing module in the present invention;

[0020] Figure 6 It is a schematic diagram of the architecture of the user feedback module in the present invention;

[0021] Figure 7 It is a schematic diagram of the architecture of the background extension module in the present invention;

[0022] Figure 8 It is a schematic diagram of the architecture of the record saving module in the present invention.

[0023] In the figure: 1. Request receiving module; 2. Information transmission module; 3. Central processing module; 4. Data storage module; 5. Instruction processing module; 6. User feedback module; 7. Background extension module; 8. Record saving module; 101. Information receiving module; 102. Data cleaning module; 103. Data integration module; 104. Information output module; 301. Data receiving module; 302. Entity extraction module; 303. Picture extraction module; 304. Character extraction module; 305. Intention recognition module; 306. Dialogue state tracking module; 307. Strategy selection module; 308. Data query module; 401. Data call module; 402. Data analysis module; 403. Result obtaining module; 404. Continuous upgrade module; 501. Personalized customization module; 502. Response generation module; 503. Text synthesis module; 504. Voice synthesis module; 505. Multimedia integration module; 601. Feedback receiving module; 602. User feedback analysis module; 603. Continuous learning module; 701. Asynchronous task processing module; 702. Automatic expansion module; 801. Data log saving module; 802. Real-time monitoring module. Specific embodiments

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] Please refer to the attached Figure 1 - attached Figure 8, an embodiment provided by the present invention: an AI customer service reply system based on cloud services, comprising a request receiving module 1, an information transmission module 2, a central processing module 3, a data storage module 4, an instruction processing module 5, a user feedback module 6, a background expansion module 7, and a record saving module 8. The request receiving module 1 is controllably connected to the information transmission module 2, the information transmission module 2 is controllably connected to the central processing module 3, and the central processing module 3 is respectively controllably connected to the data storage module 4, the instruction processing module 5, the user feedback module 6, the background expansion module 7, and the record saving module 8. The user feedback module 6 and the record saving module 8 are controllably connected to the data storage module 4; the request receiving module 1 is composed of an information receiving module 101, a data cleaning module 102, a data integration module 103, and an information output module 104. The information receiving module 101 is controllably connected to the data cleaning module 102, the data cleaning module 102 is controllably connected to the data integration module 103, and the data integration module 103 is controllably connected to the information output module 104; the central processing module 3 is composed of a data receiving module 301, an entity extraction module 302, a picture extraction module 303, a text extraction module 304, an intent recognition module 305, a dialogue state tracking module 306, a policy selection module 307, and a data query module 308. The data receiving module 301 is controllably connected to the entity extraction module 302, and the entity extraction module 302 is respectively controllably connected to the picture extraction module 303 and the text extraction module 304; the picture extraction module 303 and the text extraction module 304 are controllably connected to the intent recognition module 305, the intent recognition module 305 is controllably connected to the dialogue state tracking module 306, the dialogue state tracking module 306 is controllably connected to the policy selection module 307, and the policy selection module 307 is controllably connected to the data query module 308; the data storage module 4 is composed of a data calling module 401, a data analysis module 402, a result obtaining module 403, and a continuous upgrade module 404. The data calling module 401 is controllably connected to the data analysis module 402, the data analysis module 402 is controllably connected to the result obtaining module 403, and the result obtaining module 403 is controllably connected to the continuous upgrade module 404; the instruction processing module 5 is composed of a personalized customization module 501, a response generation module 502, a text synthesis module 503, a voice synthesis module 504, and a multimedia integration module 505. The personalized customization module 501 is controllably connected to the response generation module 502, and the response generation module 502 is controllably connected to the text synthesis module 503; the response generation module 502 is respectively controllably connected to the voice synthesis module 504 and the multimedia integration module 505; the user feedback module 6 is composed of a feedback receiving module 601, a user feedback analysis module 602, and a continuous learning module 603. The feedback receiving module 601 is controllably connected to the user feedback analysis module 602, and the user feedback analysis module 602 is controllably connected to the continuous learning module 603;The background extension module 7 is composed of an asynchronous task processing module 701 and an automatic extension module 702. The asynchronous task processing module 701 controls the connection to the automatic extension module 702. The record saving module 8 is composed of a data log saving module 801 and a real-time monitoring module 802. The data log saving module 801 controls the connection to the real-time monitoring module 802.;

[0026] Specifically, when in use, first, the information receiving module 101 in the request receiving module 1 receives user information through channels such as website chat boxes, mobile applications, and social media. The data is preprocessed in the data cleaning module 102 and the data integration module 103, and the preprocessed information is output in the information output module 104 and transmitted to the data receiving module 301 in the central processing module 3 through the information transmission module 2. The entity extraction module 302, the picture extraction module 303, and the text extraction module 304 respectively extract the information of pictures and texts. In the intent recognition module 305, NLP technology is used to parse the user's input to determine the user's intent or request type. In the dialogue state tracking module 306, the state of the current dialogue is maintained to ensure context consistency in complex interactions. In the policy selection module 307, the corresponding policy is selected according to the current situation. In the data query module 308, the stored product content or training results are called; in the personalized customization module 501 in the instruction processing module 5, the response content is adjusted according to factors such as user preferences and historical records to provide a personalized service experience. In the response generation module 502, the system's answer is converted into a natural and fluent language expression. In the text synthesis module 503, the voice synthesis module 504, and the multimedia integration module 505, content in the form of text, voice, pictures, links, or other forms can be selected as supplementary explanations according to user preferences, which can be customized according to user preferences and can improve the user experience; in the feedback receiving module 601 in the user feedback module 6, the evaluation of the user on this service is received. In the user feedback analysis module 602, the level of the user's evaluation of a certain problem is analyzed. In the continuous learning module 603, machine learning algorithms are used to continuously optimize the model performance to adapt to new language patterns and changes in user needs; in the data log saving module 801 in the record saving module 8, all interaction records are recorded for subsequent analysis, troubleshooting, and compliance review. In the real-time monitoring module 802, an alarm mechanism is set to monitor the health status of the system and the compliance with the service level agreement SLA; in the data call module 401 in the data storage module 4, the user request data within a certain time is retrieved. In the data analysis module 402, statistical analysis is performed on the data. In the result obtaining module 403, results are obtained according to the information in the statistical chart. In the continuous upgrade module 404, the product or service is upgraded according to the obtained results, which is beneficial to the improvement of the product and service; in the asynchronous task processing module 701 in the background extension module 7, for complex queries or long-running tasks, they can be placed in the background queue for asynchronous execution. In the automatic expansion module 702, when the traffic increases, the cloud service platform can automatically add computing resources according to preset rules to ensure service quality and is beneficial to coping with traffic peaks.

[0027] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. An artificial intelligence (AI) customer service response system based on cloud services, comprising a request receiving module (1), an information transmission module (2), a central processing module (3), a data storage module (4), an instruction processing module (5), a user feedback module (6), a background expansion module (7) and a record keeping module (8), characterized in that: The request receiving module (1) controls the connection to the information transmission module (2), the information transmission module (2) controls the connection to the central processing module (3), the central processing module (3) respectively controls the connection to the data storage module (4), the instruction processing module (5), the user feedback module (6), the background expansion module (7) and the record preservation module (8), and the user feedback module (6) and the record preservation module (8) control the connection to the data storage module (4).

2. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The request receiving module (1) is composed of an information receiving module (101), a data cleaning module (102), a data integration module (103) and an information output module (104); the information receiving module (101) controls the connection to the data cleaning module (102); the data cleaning module (102) controls the connection to the data integration module (103); and the data integration module (103) controls the connection to the information output module (104).

3. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The central processing module (3) is composed of a data receiving module (301), an entity extraction module (302), an image extraction module (303), a text extraction module (304), an intention recognition module (305), a dialogue state tracking module (306), a strategy selection module (307) and a data query module (308). The data receiving module (301) controls the connection to the entity extraction module (302), and the entity extraction module (302) controls the connection to the image extraction module (303) and the text extraction module (304) respectively.

4. The artificial intelligence (AI) customer service response system based on cloud services according to claim 3, characterized in that: The image extraction module (303) and the text extraction module (304) control the connection intention recognition module (305), the intention recognition module (305) controls the connection dialogue state tracking module (306), the dialogue state tracking module (306) controls the connection strategy selection module (307), and the strategy selection module (307) controls the connection data query module (308).

5. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The data storage module (4) is composed of a data calling module (401), a data analysis module (402), a result obtaining module (403) and a continuous upgrading module (404). The data calling module (401) controls the connection to the data analysis module (402), the data analysis module (402) controls the connection to the result obtaining module (403), and the result obtaining module (403) controls the connection to the continuous upgrading module (404).

6. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The instruction processing module (5) is composed of a personalized customization module (501), a response generation module (502), a text synthesis module (503), a speech synthesis module (504) and a multimedia integration module (505). The personalized customization module (501) controls the connection response generation module (502), and the response generation module (502) controls the connection text synthesis module (503).

7. The artificial intelligence (AI) customer service response system based on cloud services according to claim 6, characterized in that: The response generation module (502) controls the connection with the speech synthesis module (504) and the multimedia integration module (505) respectively.

8. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The user feedback module (6) is composed of a feedback receiving module (601), a user feedback analysis module (602) and a continuous learning module (603). The feedback receiving module (601) controls the connection to the user feedback analysis module (602), and the user feedback analysis module (602) controls the connection to the continuous learning module (603).

9. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The background expansion module (7) is composed of an asynchronous task processing module (701) and an automatic expansion module (702), and the asynchronous task processing module (701) controls the connection with the automatic expansion module (702).

10. The artificial intelligence (AI) customer service response system based on cloud services according to claim 1, characterized in that: The record storage module (8) is composed of a data log storage module (801) and a real-time monitoring module (802), and the data log storage module (801) controls the connection with the real-time monitoring module (802).

Images