User demand analysis and response system based on artificial intelligence

Abstract

The invention discloses a user demand analysis and response system based on artificial intelligence, and belongs to the field of Internet, the user demand analysis and response system comprises a user demand acquisition module, a judgment analysis module, an intelligent response generation module and a feedback module, the user demand acquisition module is used for integrating multi-source data such as webpage end text input, mobile end voice instructions and social platform private messages, and the judgment analysis module is used for judging and analyzing the multi-source data; and the judgment and analysis module is used for judging and analyzing an instruction which is received and converted by the user demand acquisition module. Based on the extensibility of an artificial intelligence condition technology, user problems are accurately solved, the production capacity is improved, the problem that user pointing is not clear is clearly solved, customer questions are quickly solved, and the user experience is improved. And meanwhile, the accurate data source meets the diversity of customer demands in the aspects of materials, equipment, application space, technical direction, market demand, actual supply level and the like, so that the customer experience and satisfaction are improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a user demand analysis and response system based on artificial intelligence. Background Art

[0002] Artificial intelligence is a discipline that studies how to use computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.). With the popularization of intelligent information processing and artificial intelligence, more and more fields are beginning to choose to use artificial intelligence customer service instead of traditional manual customer service. This artificial intelligence customer service model can not only save labor costs but also achieve standardized responses to customer needs. It is also the future development trend of customer service work.

[0003] Nowadays, users usually interact frequently with various service platforms, and their consulting needs are complex and diverse. Traditional response solutions are often based on simple keyword matching, which makes it difficult to understand semantically ambiguous and context-sensitive needs, resulting in low response accuracy and poor user experience. Summary of the invention

[0004] The purpose of the present invention is to propose an artificial intelligence-based user demand analysis and response system to solve the problem that users nowadays often interact frequently with various service platforms and have complex and diverse consulting needs. Traditional response solutions are often based on simple keyword matching, which makes it difficult to understand semantically ambiguous and context-sensitive needs, resulting in low response accuracy and poor user experience.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technologies: a user demand analysis and response system based on artificial intelligence, including a user demand acquisition module, a judgment analysis module, an intelligent response generation module and a feedback module;

[0006] The user demand collection module is used to integrate multi-source data such as web page text input, mobile voice commands, and social platform private messages, and convert them into standard text after noise reduction and format normalization preprocessing;

[0007] The judgment and analysis module is used to judge and analyze the instructions received and converted by the user demand acquisition module, and then output the correct instructions to the intelligent response generation module;

[0008] The intelligent answer generation module is used to search the local pre-built knowledge base and match the corresponding answer template for the classified and confirmed needs. It can also use the generative artificial intelligence model to automatically generate the answer text that fits the user's needs.

[0009] The feedback module is used to collect users' ratings, comments, and follow-up information on the response content. Based on the back propagation of feedback data, the model parameters of the semantic analysis, demand classification, and response generation links in the system are adjusted and optimized.

[0010] As a further description of the above technical solution: The intelligent response generation module includes a response transfer module, and the response transfer module is used to transfer to a human customer service for response.

[0011] As a further description of the above technical solution: The judgment and analysis module includes a semantic analysis unit, and the semantic analysis unit is used to connect to a knowledge graph database to improve the accuracy of demand analysis.

[0012] As a further description of the above technical solution: The user demand collection module includes an information storage unit, and the information storage unit is used to store user information data.

[0013] As a further description of the above technical solution: The user demand collection module includes a timing unit, and the timing unit is used to preset a time value.

[0014] As a further description of the above technical solution: The intelligent response generation module can integrate the user's historical interaction preferences, adjust the language style and expression mode of the response text, and achieve personalized responses.

[0015] As a further description of the above technical solution: The judgment and analysis module further includes a language processing unit, and the language processing unit is used to perform word segmentation, part-of-speech tagging, and syntactic analysis on the standard text, construct a semantic dependency tree, and mine the deep semantic relationships of the text.

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0017] Based on the extensibility of artificial intelligence conditional technology, it can accurately solve user problems, improve production capacity, clearly solve the problem of unclear user directions, quickly answer customer questions, and at the same time, the accurate data source realizes the diversity of meeting the needs of each customer from aspects such as materials, equipment, application space, technology direction, market demand, and actual supply level, thereby improving customer experience and satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Shows a schematic system flow diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to 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.

[0020] Refer toFigure 1 , the user demand analysis and response system based on artificial intelligence provided in this embodiment includes a user demand collection module, a judgment and analysis module, an intelligent response generation module, and a feedback module;

[0021] The user demand collection module is used to integrate multi-source data such as web page text input, mobile voice commands, and social platform private messages, and after preprocessing such as noise reduction and format normalization, convert it into standard text;

[0022] The judgment and analysis module is used to judge and analyze the instructions received and converted by the user demand collection module, and then output the correct instructions to the intelligent response generation module;

[0023] The intelligent response generation module is used to first retrieve the pre-built knowledge base locally for the classified and determined requirements, and match the corresponding answer templates; at the same time, it can also rely on the generative artificial intelligence model to automatically generate response texts that meet the user's needs;

[0024] The feedback module is used to collect the user's ratings, comments, and follow-up question information for the response content, and based on the backpropagation of the feedback data, adjust and optimize the model parameters of each link in the system, including semantic analysis, demand classification, and response generation.

[0025] Among them, first, the user inputs data instructions through methods such as keyboard and voice input, passwords, voice, pictures, videos, and documents. Subsequently, the user demand collection module converts the data instructions into a unified text format. Then, through the semantic analysis unit in the judgment and analysis module, using natural language processing algorithms, the unified text is segmented, part-of-speech tagged, syntactic analyzed, a semantic dependency tree is constructed, and the deep semantic relationship of the text is mined to analyze the user's true demand intention. At the same time, associated knowledge is queried from the knowledge graph to supplement semantic information, correct the deviation in demand understanding, and improve the accuracy of demand analysis. Then, the analyzed instructions are passed into the intelligent response generation module. Then, for the determined requirements, first retrieve the pre-built knowledge base locally and match the corresponding answer templates; if there is no match, then rely on the generative artificial intelligence model to automatically generate a response text that meets the user's needs and has a natural language style. At the same time, according to the user's historical interaction preferences, adjust the language style and expression of the response text to achieve personalized responses. Finally, the feedback module collects the ratings, comments, and follow-up question information for the response content, and based on the backpropagation of the feedback data, adjusts and optimizes the model parameters of each link in the system, including semantic analysis, demand classification, and response generation.

[0026] Specifically, the intelligent response generation module includes a response transfer module, and the response transfer module is used to transfer to an artificial customer service for response.

[0027] Among them, when the user encounters difficulties during use or the device is damaged, they can switch to manual customer service to ease the customer's emotions and avoid giving the customer a bad experience.

[0028] Specifically, the judgment analysis module includes a semantic analysis unit, which is used to connect to a knowledge graph database to improve the accuracy of demand analysis.

[0029] Among them, it can query related knowledge from the knowledge graph based on the entity information in the text of the knowledge graph database, supplement semantic information, correct the deviation in demand understanding, and improve the accuracy of demand analysis.

[0030] Specifically, the user demand collection module includes an information storage unit, and the information storage unit is used to store user information data.

[0031] The historical user information data is continuously stored through the information storage unit so as to judge whether the next user is a new user, and to push answers based on the previous user consultation habits.

[0032] Specifically, the user demand collection module includes a timing unit, and the timing unit is used to preset a time value.

[0033] Among them, through the preset time value, when the user is in the process of voice input, when the interval time is less than or equal to the preset value, it is judged as an intermittent pause and the voice input is defective. When the interval time is greater than the preset value, it is judged that the voice command input is completed, thereby ensuring the integrity of the voice information.

[0034] Specifically, the intelligent response generation module can integrate the user's historical interaction preferences, adjust the language style and expression method of the response text, and achieve personalized responses.

[0035] Among them, by adjusting the language style, the user experience is greatly improved, avoiding causing users to feel unhappy when using the product.

[0036] Specifically, the judgment and analysis module also includes a language processing unit, which is used to perform word segmentation, part-of-speech tagging, and syntactic analysis on the standard text, build a semantic dependency tree, and mine the deep semantic relationship of the text.

[0037] Among them, the language processing unit fully analyzes the user's words to better analyze the user's real needs and intentions and better answer the user's doubts.

[0038] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. User demand analysis and response system based on artificial intelligence, including user demand collection module, judgment analysis module, intelligent response generation module and feedback module; The user demand collection module is used to integrate multi-source data such as web page text input, mobile voice commands, and social platform private messages, and convert them into standard text after noise reduction and format normalization preprocessing; The judgment and analysis module is used to judge and analyze the instructions received and converted by the user demand acquisition module, and then output the correct instructions to the intelligent response generation module; The intelligent answer generation module is used to search the local pre-built knowledge base and match the corresponding answer template for the classified and confirmed needs. It can also use the generative artificial intelligence model to automatically generate the answer text that fits the user's needs. The feedback module is used to collect users' ratings, comments, and follow-up information on the response content. Based on the back propagation of feedback data, the model parameters of the semantic analysis, demand classification, and response generation links in the system are adjusted and optimized.

2. The user demand analysis and response system based on artificial intelligence according to claim 1 is characterized in that: The intelligent response generation module includes a response transfer module, which is used to transfer the response to the manual customer service.

3. The user demand analysis and response system based on artificial intelligence according to claim 1 is characterized in that: The judgment analysis module includes a semantic analysis unit, which is used to connect to a knowledge graph database to improve the accuracy of demand analysis.

4. The user demand analysis and response system based on artificial intelligence according to claim 1 is characterized in that: The user demand collection module includes an information storage unit, and the information storage unit is used to store user information data.

5. The user demand analysis and response system based on artificial intelligence according to claim 1 is characterized in that: The user demand collection module includes a timing unit, and the timing unit is used to preset a time value.

6. The user demand analysis and response system based on artificial intelligence according to claim 1 is characterized in that: The intelligent response generation module can integrate the user's historical interaction preferences, adjust the language style and expression method of the response text, and realize personalized response.

7. The user demand analysis and response system based on artificial intelligence according to claim 1 is characterized in that: The judgment and analysis module also includes a language processing unit, which is used to perform word segmentation, part-of-speech tagging, and syntactic analysis on the standard text, build a semantic dependency tree, and mine the deep semantic relationship of the text.

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