Intelligent visual configuration method and system for investment attraction demand

Abstract

The invention relates to the technical field of network configuration, in particular to an intelligent visual configuration method and system for investment attraction demands, and the method comprises the steps: obtaining the investment attraction demands of an investment attraction customer; performing semantic analysis on the investment attraction demand and each condition in a pre-constructed investment attraction condition library to generate a structured demand condition matrix; disassembling the structured demand condition matrix, dividing each condition in the matrix into a hard condition and a soft condition, and endowing the soft condition with a weight dimension; presenting the structured demand condition matrix to a customer in a visual condition list mode; dynamically adjusting the visual condition list based on the self demand of the customer; and displaying the final visual condition list after dynamic adjustment. According to the method and the device, the problems of tedious investment attraction demand input, opaque matching and difficulty in flexible adjustment in the prior art can be solved, the matching efficiency and accuracy are improved, and the trust of a customer to a matching result is enhanced.

Description

Technical Field

[0001] The present application relates to the field of network configuration technology, and in particular to a method and system for intelligent visualization configuration of investment promotion needs. Background Art

[0002] With the continuous development of the investment promotion field, the needs of corporate customers for investment projects are becoming increasingly diversified and complex. In order to improve the efficiency and accuracy of project matching, investment promotion platforms have gradually introduced digital technologies to assist demand matching through data processing and algorithm analysis. However, the diversity and personalization of customer needs have posed new challenges to traditional investment promotion demand entry and matching methods, and more efficient and intelligent solutions are urgently needed to adapt to complex business scenarios.

[0003] Existing technologies usually use fixed forms to let customers input demand information. The data is entered through the input module and stored in the system database. Based on the stored demand data, the system uses a preset matching algorithm to recommend related projects. The matching results are usually presented to customers in the form of lists or charts. The entire process includes data input, storage, calculation, output and other links, with a certain degree of automation, and can meet the basic needs of customers within a certain range.

[0004] However, in the existing technology, the way to input customer needs is relatively cumbersome, and it is difficult to express complex needs quickly and intuitively. At the same time, the operation process of the matching algorithm is usually opaque, and it is difficult for customers to understand the matching logic and flexibly adjust the matching conditions. This inconvenience leads to a decrease in customer trust in the matching results, thus affecting the efficiency and effectiveness of investment promotion work. Summary of the invention

[0005] This application provides a method and system for intelligent visualization configuration of investment demand, which can solve the problems of cumbersome investment demand input, opaque matching and difficulty in flexible adjustment in the prior art, improve the efficiency and accuracy of matching, and enhance customers' trust in matching results. This application provides the following technical solutions:

[0006] In a first aspect, the present application provides a method for intelligent visualization configuration of investment promotion demand, the method comprising:

[0007] Obtain investment needs of investment clients;

[0008] Perform semantic analysis on the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix;

[0009] Decomposing the structured demand condition matrix, dividing each condition in the matrix into hard conditions and soft conditions, and assigning weight dimensions to the soft conditions;

[0010] Presenting the structured requirement condition matrix to the customer in the form of a visual condition list;

[0011] Dynamically adjust the visualization condition list based on the customer's own needs;

[0012] Displays the final list of visual conditions after dynamic adjustment.

[0013] In a specific implementation scheme, obtaining the investment demand of investment clients includes:

[0014] The customer's demand information is received through the data input module, and the customer enters the demand information in the form of voice input or text input.

[0015] In a specific possible implementation scheme, the semantic analysis of the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix includes:

[0016] Pre-build a business conditions database, which covers various needs in the business field;

[0017] Use the semantic similarity calculation method to calculate the semantic similarity between the texts of multiple investment requirements and each condition in the investment condition database, and match the most similar conditions;

[0018] Arrange the multiple matched conditions according to logical rules to generate a structured requirement condition matrix.

[0019] In a specific possible implementation scheme, the structured demand condition matrix is ​​decomposed, each condition in the matrix is ​​divided into hard conditions and soft conditions, and the soft conditions are assigned weight dimensions including:

[0020] Automatically decompose the structured demand condition matrix and divide the conditions in the matrix into hard conditions and soft conditions. Hard conditions are clear and non-negotiable constraints, while soft conditions are conditions with flexible space.

[0021] Assign a weight value to each soft condition based on the selection frequency and weight preference of past requirements.

[0022] In a specific implementation scheme, presenting the structured requirement condition matrix to the customer in the form of a visual condition list includes:

[0023] The divided hard and soft conditions are organized into a condition list according to the logical structure and hierarchical relationship. Each condition in the list corresponds to the specific requirements input by the customer.

[0024] Sort your condition lists by category and priority using a variety of presentation methods.

[0025] In a specific implementation scheme, dynamically adjusting the visualization condition list based on the customer's own needs includes:

[0026] Allows adding or deleting certain conditional items;

[0027] Allows you to adjust the position of conditional items in the list by dragging;

[0028] For some conditions, numerical adjustment function is provided;

[0029] Provides real-time preview function.

[0030] In a specific implementation scheme, the final visualization condition list after the dynamic adjustment includes:

[0031] Provide a transparent display of the matching algorithm to explain to customers the relationship between each requirement and the recommended investment project;

[0032] Use diagrams, text descriptions or logical links to show how to match based on customer demand conditions and the impact of each condition on the final result.

[0033] In the second aspect, the present application provides an intelligent visualization configuration system for investment promotion needs, which adopts the following technical solutions:

[0034] An intelligent visualization configuration system for investment promotion needs, comprising:

[0035] Demand acquisition module, used to obtain investment needs of investment clients;

[0036] A semantic analysis module, used to perform semantic analysis on the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix;

[0037] A condition decomposition module is used to decompose the structured demand condition matrix, divide each condition in the matrix into hard conditions and soft conditions, and assign a weight dimension to the soft conditions;

[0038] An initial presentation module, used to present the structured requirement condition matrix to the customer in the form of a visual condition list;

[0039] A dynamic adjustment module, used to dynamically adjust the visualization condition list based on the customer's own needs;

[0040] The final display module is used to display the final visualization condition list after dynamic adjustment.

[0041] In a third aspect, the present application provides an electronic device, comprising a processor and a memory; the memory stores a program, and the program is loaded and executed by the processor to implement a method for intelligent visualization configuration of investment promotion needs as described in the first aspect.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium, in which a program is stored. When the program is executed by a processor, it is used to implement a method for intelligent visualization configuration of investment promotion needs as described in the first aspect.

[0043] In summary, the beneficial effects of this application include at least:

[0044] 1) By supporting both voice input and text input, and combining voice recognition and auto-completion functions, the customer's demand input process is greatly simplified. Customers can quickly express complex or diverse demands through voice, reducing the tedious steps of traditional text input. At the same time, the text input module also has error correction and auto-completion functions to ensure that the input demands are accurate. This technical effect effectively improves the user experience and input efficiency, and is particularly suitable for scenarios in the field of investment promotion where the demands are complex and the expressions are diverse.

[0045] 2) Through semantic analysis technology, customer needs are converted into a structured demand condition matrix, and hard conditions and soft conditions are clearly distinguished. The matching results are not only displayed to customers, but also a list of conditions is presented in a visual way, and the impact of each demand condition on the recommendation results is explained in detail. The transparency and explainability of this process allow customers to understand the logic of the matching algorithm, enhance customers' trust in the matching results, and improve the use value and customer satisfaction of the investment promotion platform.

[0046] 3) Customers can flexibly adjust the condition list on the visual interface according to their own needs, including adding, subtracting, dragging, adjusting values ​​and other operations. Through the real-time preview and feedback function, customers can immediately see the impact of the adjustment on the matching results, so that the demand more accurately reflects their actual needs. This dynamic adjustment function supports personalized customization of needs, and can better adapt to the changes and diversified needs of customers in actual operations, thereby providing more accurate and personalized investment project recommendations, further improving the adaptability and flexibility of the system.

[0047] Receive the client's investment demand through a variety of demand input methods, and use semantic analysis technology to match the demand with the conditions in the pre-built investment condition library to generate a structured demand condition matrix. Further classify the conditions into hard and soft conditions, and assign weights to the soft conditions. Finally, present the condition list in a visual way to support customers to dynamically adjust the conditions according to actual needs. This solution solves the problems of cumbersome investment demand input, opaque matching and difficulty in flexible adjustment in the existing technology by enhancing the convenience of demand expression, transparent matching process and flexible adjustment of conditions, improves the efficiency and accuracy of matching, and enhances customer trust in matching results.

[0048] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present application in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flow chart of the intelligent visualization configuration method for investment promotion needs in the embodiment of the present application.

[0050] Figure 2 It is a schematic diagram of the overall process of the intelligent visualization configuration method for investment promotion needs in the embodiment of the present application.

[0051] Figure 3 It is a structural block diagram of the intelligent visualization configuration system for investment promotion needs in the embodiment of the present application.

[0052] Figure 4 It is a block diagram of an electronic device with intelligent visualization configuration for investment promotion needs in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0054] Optionally, the present application uses the intelligent visualization configuration method for investment promotion needs provided in each embodiment as an example for explanation in an electronic device, where the electronic device is a terminal or a server. The terminal may be a mobile phone, a computer, a tablet computer, etc. This embodiment does not limit the type of electronic device.

[0055] Reference Figure 1 , is a flow chart of a method for intelligent visualization configuration of investment promotion needs provided by an embodiment of the present application, and the method includes at least the following steps:

[0056] Step S101: Obtain the investment needs of investment clients.

[0057] In step 101, the customer's demand information is received through the data input module, and multiple forms of demand expression are supported to simplify the customer's input operation. One is that the customer can submit the investment demand through voice input. Through the built-in voice recognition module, the customer's voice content is converted into corresponding text information. The voice input method can effectively reduce the complexity of text input, which is particularly suitable for describing complex or diverse needs, and improves the convenience of operation. Another is that the customer can directly enter the demand information in the form of text, including filling in an open text box or selecting a preset option. The text input module supports automatic completion and error correction functions to improve input efficiency and ensure the accuracy of information. At the same time, the module supports customers to express their needs freely according to their own habits, without strictly following a fixed format, which further simplifies the operation process.

[0058] Step S102: semantically analyze the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix.

[0059] In step S102, a merchant invitation condition library is pre-constructed, and the merchant invitation condition library covers various common requirements and their associated key conditions in the merchant invitation field, such as investment scale, industry field, geographical location, etc., and the merchant invitation condition library is regularly updated to continuously improve various conditions. After obtaining the merchant invitation demand input by the merchant invitation user, the semantic similarity between the text of the merchant invitation demand and each condition in the merchant invitation condition library is calculated using the semantic similarity calculation method, and the most similar condition is matched. In implementation, since there are several merchant invitation demands input by the merchant invitation user, multiple conditions are matched. Finally, the matched multiple conditions are sorted according to certain logical rules to generate a structured demand condition matrix. The structured matrix further clarifies the meaning and hierarchical relationship of each condition, and provides standardized basic data for subsequent processing.

[0060] Optionally, the cosine similarity is used in the present application to calculate the semantic similarity, and other methods may be used to calculate the semantic similarity. The present application does not limit the method for calculating the semantic similarity.

[0061] In another feasible embodiment, the following formula may also be used to calculate the semantic similarity Sim(Q, C) between the investment demand text and each condition text in the investment condition library:

[0062]

[0063] Among them, Q is the investment demand text, C is the conditional text, cos(v Q ,v C ) is the cosine similarity between the requirement text and the condition text, v Q and v CThey are the overall word vector representations of the requirement text and conditional text, which are generated using the existing BERT model in this application. Qi and v Cj are the word vector representation of the i-th word in the requirement text and the word vector representation of the j-th word in the condition text, cos(v Qi ,v Cj ) is the cosine similarity between the word vector representation of the i-th word in the demand text and the word vector representation of the j-th word in the condition text. m and n are the number of words in the investment demand text and the condition text respectively. α and β are weight coefficients, which add up to 1 and are used to balance the influence of the overall semantic similarity and the semantic similarity between word pairs. They can be adjusted according to needs. The condition with the largest value calculated at the end is the most similar condition.

[0064] In the above formula, by calculating the overall cosine similarity of the requirement text and the conditional text, the approximate matching degree of the two at the semantic level can be evaluated. This part reflects the overall semantic association between the requirement text and the conditional text, ensuring that the system can identify the conditions that match the requirements. The word pair similarity between the requirement text and the conditional text is calculated word by word. By calculating the cosine similarity of all word vectors, the detailed matching in the text can be deeply captured, avoiding the keyword matching problem that may be ignored by relying only on global semantics. This is especially important for complex requirements with subtle differences.

[0065] Step S103: decompose the structured demand condition matrix, divide each condition in the matrix into hard conditions and soft conditions, and assign weight dimensions to the soft conditions.

[0066] In step S103, the structured demand condition matrix is ​​automatically disassembled, and each condition in the matrix is ​​divided into two categories: hard conditions and soft conditions, and the soft conditions are given weight dimensions. Specifically, first, those conditions with clear and non-negotiable constraints are automatically identified, such as "the investment amount must be above a certain threshold" or "the project must be located in a certain place", and the necessary conditions are used as hard conditions. Then, for conditions with a certain elastic space, such as "preferring a certain type of enterprise" or "the investment amount is in a certain range", they are used as soft conditions, and a weight value is given to each soft condition based on the selection frequency and weight preference of past needs. The size of the weight value reflects the importance of the condition to the matching result. The weight allocation method can be based on the subjective score provided by the customer, or combined with the priority reference of industry data. The divided hard conditions and soft conditions are organized into two parts for display. As rigid constraints, hard conditions will directly affect the screening scope of the project; soft conditions are used as matching bonus items to affect the priority ranking of the screening results. Through the decomposition and classification of this step, the core constraints and flexible space of customer needs can be clearly presented, providing effective input conditions for subsequent precise matching, while improving the interpretability and transparency of the matching algorithm.

[0067] Step S104: present the structured requirement condition matrix to the customer in the form of a visual condition list.

[0068] In step S104, the divided hard and soft conditions are generated into a condition list according to the logical structure and hierarchical relationship. Each condition in the list corresponds to the specific needs entered by the customer. Hard conditions are usually displayed in the form of "required items", and customers must meet these conditions before further matching or recommendation; soft conditions are displayed as "optional items" or "recommended items", and can be adjusted and optimized according to customer needs. Through a graphical interface, a variety of display methods such as tables, lists, labels, cards, etc. are used to sort the condition list by category and priority, so that customers can view all demand conditions at a glance.

[0069] Step S105: dynamically adjust the visualization condition list based on the customer's own needs.

[0070] In step S105, customers can make dynamic adjustments on the provided visual condition list interface according to their specific needs to ensure that the needs more accurately reflect their actual needs. Specifically, customers can add or delete certain condition items according to changes in actual needs. For example, if customers realize that the importance of certain conditions to the project has changed, they can add relevant conditions through interface operations; conversely, if certain conditions are no longer applicable, they can be deleted or set to no longer be used. At the same time, customers can adjust the position of condition items in the list by dragging. For example, customers can move some more important conditions to the top of the list, or move less important conditions down, so as to highlight key needs. Drag-and-drop operations can help customers manage and organize demand items in a more flexible way and improve user experience. For some conditions, a numerical adjustment function is provided. Customers can directly increase, decrease or fine-tune numerical conditions in the list. For example, customers can adjust the numerical range of certain conditions, or set the weight, priority, etc. of conditions to better match actual needs. In addition, a real-time preview function is provided, and customers can see the adjustment results immediately when adjusting the demand conditions. The displayed information in the list is automatically updated, and the adjusted demand matching effect may be fed back to customers in a visual way. For example, adjusting a certain condition may affect the matching results. The result changes can be displayed through color, progress bars, or icons to let customers understand the impact of the adjustment.

[0071] Step S106: display the final visualization condition list after dynamic adjustment.

[0072] In step S106, the requirements that have been dynamically adjusted and optimized by the customer are integrated into a final list of conditions and presented to the customer in a clear and concise manner. At the same time, a transparent display of the matching algorithm is provided to explain to the customer the relationship between each requirement and the recommended investment project. Through charts, text descriptions or logical link displays, customers can clearly see how the system matches based on the customer's requirements and the impact of each condition on the final result. The transparent display mechanism enables customers to understand the matching process and increase trust.

[0073] In summary, combined with Figure 2 , receiving the client's investment promotion needs through a variety of demand input methods, and using semantic analysis technology to match the needs with the conditions in the pre-built investment promotion condition library to generate a structured demand condition matrix. Further classify the conditions into hard and soft conditions, and assign weights to the soft conditions. Finally, present the condition list in a visual way to support customers to dynamically adjust the conditions according to actual needs. This solution solves the problems of cumbersome investment promotion demand input, opaque matching and difficulty in flexible adjustment in the existing technology by enhancing the convenience of demand expression, transparent matching process and flexible adjustment of conditions, improves the efficiency and accuracy of matching, and enhances customer trust in matching results.

[0074] Figure 3 This is a structural diagram of an intelligent visualization configuration system for investment promotion needs provided by an embodiment of the present application. The system includes at least the following modules:

[0075] Demand acquisition module, used to obtain investment needs of investment clients;

[0076] The semantic analysis module is used to perform semantic analysis on the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix;

[0077] The condition decomposition module is used to decompose the structured demand condition matrix, divide the conditions in the matrix into hard conditions and soft conditions, and assign weight dimensions to the soft conditions;

[0078] The initial presentation module is used to present the structured requirement matrix to customers in the form of a visual condition list;

[0079] Dynamic adjustment module, used to dynamically adjust the visual condition list based on the customer's own needs;

[0080] The final display module is used to display the final visualization condition list after dynamic adjustment.

[0081] For relevant details, refer to the above method embodiment.

[0082] Figure 44 is a block diagram of an electronic device provided by an embodiment of the present application. The device at least includes a processor 401 and a memory 402.

[0083] The processor 401 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 401 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 401 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 401 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 401 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0084] The memory 402 may include one or more computer-readable storage media, which may be non-transitory. The memory 402 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 402 is used to store at least one instruction, which is used to be executed by the processor 401 to implement the intelligent visualization configuration method for investment promotion needs provided in the method embodiment of the present application.

[0085] In some embodiments, the electronic device may further optionally include: a peripheral device interface and at least one peripheral device. The processor 401, the memory 402 and the peripheral device interface may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface via a bus, a signal line or a circuit board. Schematically, the peripheral devices include but are not limited to: a radio frequency circuit, a touch display screen, an audio circuit, and a power supply.

[0086] Of course, the electronic device may also include fewer or more components, which is not limited in this embodiment.

[0087] Optionally, the present application also provides a computer-readable storage medium, in which a program is stored, and the program is loaded and executed by a processor to implement the method for intelligent visualization configuration of investment promotion needs in the above method embodiment.

[0088] Optionally, the present application also provides a computer product, which includes a computer-readable storage medium, in which a program is stored, and the program is loaded and executed by a processor to implement the method for intelligent visualization configuration of investment promotion needs of the above method embodiment.

[0089] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for intelligent visualization configuration of investment promotion demand, characterized in that: The method comprises: Obtain investment needs of investment clients; Perform semantic analysis on the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix; Decomposing the structured demand condition matrix, dividing each condition in the matrix into hard conditions and soft conditions, and assigning weight dimensions to the soft conditions; Presenting the structured requirement condition matrix to the customer in the form of a visual condition list; Dynamically adjust the visualization condition list based on the customer's own needs; Displays the final list of visual conditions after dynamic adjustment.

2. The intelligent visualization configuration method for investment promotion demand according to claim 1 is characterized in that: The investment needs for acquiring investment clients include: The customer's demand information is received through the data input module, and the customer enters the demand information in the form of voice input or text input.

3. The intelligent visualization configuration method for investment promotion demand according to claim 1 is characterized in that: The semantic analysis of the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix includes: Pre-build a business conditions database, which covers various needs in the business field; Use the semantic similarity calculation method to calculate the semantic similarity between the texts of multiple investment requirements and each condition in the investment condition database, and match the most similar conditions; Arrange the multiple matched conditions according to logical rules to generate a structured requirement condition matrix.

4. The intelligent visualization configuration method for investment promotion demand according to claim 1 is characterized in that: The structured demand condition matrix is ​​decomposed, each condition in the matrix is ​​divided into hard conditions and soft conditions, and the soft conditions are given weight dimensions including: Automatically decompose the structured demand condition matrix and divide the conditions in the matrix into hard conditions and soft conditions. Hard conditions are clear and non-negotiable constraints, while soft conditions are conditions with flexible space. Assign a weight value to each soft condition based on the selection frequency and weight preference of past requirements.

5. The intelligent visualization configuration method for investment promotion demand according to claim 1 is characterized in that: The presenting the structured requirement condition matrix to the customer in the form of a visual condition list includes: The divided hard and soft conditions are organized into a condition list according to the logical structure and hierarchical relationship. Each condition in the list corresponds to the specific requirements input by the customer. Sort your condition lists by category and priority using a variety of presentation methods.

6. The intelligent visualization configuration method for investment promotion demand according to claim 1 is characterized in that: The dynamically adjusting the visualization condition list based on the customer's own needs includes: Allows adding or deleting certain conditional items; Allows you to adjust the position of conditional items in the list by dragging; For some conditions, numerical adjustment function is provided; Provides real-time preview function.

7. The intelligent visualization configuration method for investment promotion demand according to claim 1 is characterized in that: The final list of visualization conditions after dynamic adjustment of the display includes: Provide a transparent display of the matching algorithm to explain to customers the relationship between each requirement and the recommended investment project; Use diagrams, text descriptions or logical links to show how to match based on customer demand conditions and the impact of each condition on the final result.

8. An intelligent visualization configuration system for investment promotion needs, characterized in that: include: Demand acquisition module, used to obtain investment needs of investment clients; A semantic analysis module, used to perform semantic analysis on the investment demand and each condition in the pre-built investment condition library to generate a structured demand condition matrix; A condition decomposition module is used to decompose the structured demand condition matrix, divide each condition in the matrix into hard conditions and soft conditions, and assign a weight dimension to the soft conditions; An initial presentation module, used to present the structured requirement condition matrix to the customer in the form of a visual condition list; A dynamic adjustment module, used to dynamically adjust the visualization condition list based on the customer's own needs; The final display module is used to display the final visualization condition list after dynamic adjustment.

9. An electronic device, characterized in that: The device includes a processor and a memory; a program is stored in the memory, and the program is loaded and executed by the processor to implement a method for intelligent visualization configuration of investment promotion needs as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a program, which, when executed by a processor, is used to implement a method for intelligent visualization configuration of investment promotion needs as described in any one of claims 1 to 7.

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