An enterprise-level application development and data management system and method based on zero-code SaaS

Abstract

The present invention discloses an enterprise-level application development and data management system and method based on zero-code SaaS, which relates to the technical field. It obtains the application development requirement information input by the user, extracts input keywords and output keywords from the user's application development requirement information; obtains the subscription and development information of components on the SaaS platform; assigns keywords to the components on the SaaS platform; selects input components and output components for the user; recommends execution components for the user; the user refers to the recommended results of the execution components and uses the input components, output components and execution components to develop the required application; there is no need for the user to purchase and maintain software, reducing the user's resource consumption and the user's maintenance burden; the user can quickly access and deploy the application program without installation and configuration; analyzes the user's requirements, combines the user's subscription information on the SaaS platform, and recommends the most suitable SaaS application development components for the user.

Description

Technical Field

[0001] The present invention relates to the technical field, and specifically to an enterprise-level application development and data management system and method based on zero-code SaaS. Background Art

[0002] SaaS (Software as a Service) is a business model that provides software application programs over the Internet. Users do not need to purchase or install software, but instead subscribe to and use software services over the Internet. This model provides enterprises with flexible, scalable, and efficient solutions, while also reducing the costs and complexities for users. In the SaaS model, users can access and use software through a browser or mobile device without installing any software on their local computers. SaaS providers are responsible for maintaining and managing the software, including tasks such as updates, upgrades, and security guarantees. By using the tools and modules provided by the SaaS platform for application design and development, enterprises can quickly and efficiently build and deploy enterprise-level applications. Therefore, how to recommend SaaS application development components to enterprises based on their application development requirements and subscription information on the SaaS platform has become an urgent problem to be solved. Summary of the Invention

[0003] The purpose of the present invention is to provide an enterprise-level application development and data management system and method based on zero-code SaaS to solve the problems raised in the prior art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: An enterprise-level application development and data management method based on zero-code SaaS, including:

[0005] S11, obtaining the application development requirement information input by the user, and extracting input keywords and output keywords from the user's application development requirement information;

[0006] S12, obtaining the subscription and development information of components on the SaaS platform, and dividing the components into input components, output components, and execution components; assigning keywords to the components on the SaaS platform; for the development information of components on the SaaS platform, without understanding the specific details, only knowing the general development uses of the components through user authorization, protecting user privacy while preventing the components from being misused;

[0007] S13, selecting input components and output components for the user according to the input keywords and output keywords; recommending execution components for the user according to the input keywords, output keywords, the user's subscription information on the SaaS platform, and the development information of the execution components;

[0008] S14, the user refers to the recommended results of the execution components and uses the input components, output components, and execution components to develop the required application.

[0009] In step S12, endowing keywords to components on the SaaS platform further includes the following steps:

[0010] Obtain the historical usage information of components on the SaaS platform, obtain the historical development requirement information of historical users from the historical usage information, and extract historical input keywords and output keywords from the historical development requirement information; add all historical input keywords and output keywords to the keyword set of the component; and calculate the concentration cen of each keyword in the keyword set of the component, cen = num1 / num, where num1 is the number of times the keyword appears in the historical usage information of the component, and num is the total number of times all keywords appear in the historical usage information of the component; if the concentration of the keyword is not less than the set threshold, retain the keyword in the keyword set of the component; if the concentration of the keyword is less than the set threshold, remove the keyword from the keyword set of the component; finally, the remaining keywords in the keyword set of the component are the keywords of the component.

[0011] In step S13, recommending execution components to users further includes the following steps:

[0012] S31, according to the input keyword and the output keyword, find all execution components that separately contain the input keyword and separately contain the output keyword, and find all execution components that simultaneously contain the input keyword and the output keyword; for the i-th execution component, if it simultaneously contains the input keyword and the output keyword, go to step S32; if it separately contains the input keyword, go to step S33, and if it separately contains the output keyword, go to step S34;

[0013] S32, let Xi represent the input keyword random variable of the i-th execution component, and Yi represent the output keyword random variable of the i-th execution component; for the execution component that simultaneously contains the input keyword and the output keyword, calculate the matching degree between the execution component and the application development requirement through the following formula, Pi = P{Xi = r ∩ Yi = y} = n(r, y, i) / N(i), where Pi is the matching degree of the i-th execution component, r and y are the input keyword and the output keyword, n(r, y, i) represents the number of times the input keyword r and the output keyword y appear simultaneously in the historical usage information of the i-th execution component, and N(i) represents the number of times the i-th execution component is used; end;

[0014] S33, for the i-th execution component that separately contains the input keyword r, determine the matching degree between the i-th execution component and the application development requirement through the following formula: The i-th execution component itself does not include the output keyword y. The matching degree between the i-th execution component and the application development requirements is calculated by means of the usage information of other execution components including the input keyword r, and the formula P{Xi = r ∩ Yi = y} is decomposed; where n is the number of execution components including the input keyword r, and W1, W2, …, Wn represent the input keyword random variables of the 1st, 2nd, …, n-th execution components including the input keyword r.

[0015] S34. For the i-th execution component that only includes the input keyword y, the matching degree between the i-th execution component and the application development requirements is determined by the following formula: The i-th execution component itself does not include the input keyword r. The matching degree between the i-th execution component and the application development requirements is calculated by means of the usage information of other execution components including the output keyword y, and the formula P{Xi = r ∩ Yi = y} is decomposed; where m is the number of execution components including the output keyword y, and V1, V2, …, Vm represent the output keyword random variables of the 1st, 2nd, …, m-th execution components including the output keyword y.

[0016] The user's requirements are reflected by the input keyword and the output keyword. The execution components that include both of these keywords can be recommended to the user for the user to judge whether to adopt them; for the execution components that only include one keyword, the matching degree is determined by using the information of other execution components including the same keyword; for example, there are 11 execution components that all include the input keyword r. Among these 11 execution components, 10 execution components also include the output keyword y at the same time. For the remaining one execution component, it can be judged that it has a high probability of also including the output keyword y. The reasons for not including the output keyword y currently may be: excessive resource consumption, fewer subscribed users; the component has been generated for a short time and has low popularity, etc.; when determining the matching degree by using the information of other execution components including the same keyword, the weight of the information of other execution components is determined according to the similarity; the same applies to the execution components including the output keyword y. The similarity is determined according to the proportion of the same keyword in all keywords. When all keywords are the same, the similarity reaches the maximum value of 1.

[0017] In step S33, the following steps are further included:

[0018] S41. The execution component Wj represents the j-th execution component containing the input keyword r. Calculate the similarity sim1(i, j) between Wj and the i-th execution component, where sim1(i, j) = (ci ∩ C1j) / (ci ∪ C1j). In the formula, ci is the keyword set of the i-th execution component, C1j is the keyword set of Wj, ci ∩ C1j represents the number of repeated keywords between Wj and the i-th execution component, and ci ∪ C1j represents the total number of keywords between Wj and the i-th execution component. Calculate the weight of Wj according to the similarity, A1j = sim1(i, j) / ∑sim1(i, j).

[0019] S42. Calculate the matching degree Pi between the i-th execution component and the application development requirement. In the formula, N(r, y, j) is the number of times the input keyword r and the output keyword y appear simultaneously in the historical usage information of Wj, and N(j) is the number of times the execution component Wj is used.

[0020] In step S34, the following steps are further included:

[0021] S43. The execution component Vk represents the k-th execution component containing the output keyword y. Calculate the similarity sim2(i, k) between Vk and the i-th execution component, where sim2(i, k) = (ci ∩ C2k) / (ci ∪ C2k). C2k is the keyword set of Vk, ci ∩ C2k represents the number of repeated keywords between Vk and the i-th execution component, and ci ∪ C2k represents the total number of keywords between Vk and the i-th execution component. Calculate the weight of Vk according to the similarity, A2k = sim2(i, k) / ∑sim2(i, k).

[0022] Calculate the matching degree Pi between the i-th execution component and the application development requirement. In the formula, N(r, y, k) is the number of times the input keyword r and the output keyword y appear simultaneously in the historical usage information of Vk, and N(k) is the number of times the execution component Vk is used.

[0023] In step S13, the step of recommending an execution component for the user further includes the following steps:

[0024] S51. Starting from the input keyword r and the output keyword y, select the input component and the output component that meet the user's requirements. Combine the matching degree between the execution component and the application development requirement to generate an application development group, which consists of an input component, an output component, and an execution component.

[0025] S52. Combine the component information subscribed by the user on the SaaS platform to determine the additional resource information consumed by the user when adopting each application development group.

[0026] In step S13, the step of recommending execution components for the user further includes the following steps:

[0027] Obtain the average matching degree information and the additional resource information consumed by each application development group. Let AVEu represent the average matching degree of the u-th application development group, and COSTu represent the additional resources consumed by the u-th application development group. Determine the average matching degree of the application development group by calculating the average value of the matching degrees between all execution components in the application development group and the application development requirements. Calculate the sub-evaluation value of each application development group, Fu = H × AVEu + L × COSTu; where H and L are weights, which are set according to the user's own situation. Sort the sub-evaluation values in descending order and recommend the application development group to the user for application development.

[0028] Usually, the user only subscribes to the services of some components on the SaaS. When recommending components for user application development, it is necessary to consider the resource consumption generated by additional component subscriptions.

[0029] To achieve the above object, the present invention provides the following technical solution: An enterprise-level application development and data management system based on zero-code SaaS, including: a SaaS platform, a data storage module, a user interaction module, and a data analysis module; the SaaS platform is connected to the data storage module, the user interaction module, and the data analysis module, and provides subscribed component services to users through the Internet; the output end of the user interaction module is connected to the input end of the data storage module, and is used to determine the user's application development requirements and recommend components that need to be subscribed to the user; the output end of the data storage module is connected to the input end of the data analysis module, and is used to store the component information subscribed by the user and the information on how components in the SaaS platform are used by the user; the data analysis module is connected to the user interaction module, and is used to analyze the matching degree between the components in the SaaS platform and the user requirements, and generate application development groups for the user to carry out application development.

[0030] The user interaction module further includes an input unit, an output unit, a selection unit, a subscription unit, and an authentication unit; the input unit is used to obtain the input keywords and output keywords of the user; the output unit is used to present the recommended application development groups to the user; the selection unit provides an interface for the user to select or reject the application development groups; the subscription unit provides a component subscription service for the user after the user selects an application development group; the authentication unit is used to identify the identity of the user. The SaaS platform further includes a component library and an application development unit: the component library is used to store the components for application development; the application development unit configures and customizes the application for the user according to the component information subscribed by the user, and provides an operation interface. The data analysis module further includes a keyword analysis unit, a component analysis unit, an application development group generation unit, and an application development group evaluation unit; the component analysis unit is used to assign keywords to the components; the keyword analysis unit is used to determine the matching degree between the components and the user's application development requirements; the application development group generation unit generates application development groups according to the input keywords, output keywords, and the matching degree between the components and the application development requirements; the application development group evaluation unit is used to determine the score value of each application development group.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: there is no need for the user to purchase and maintain software, which reduces the resource consumption of the user and the maintenance burden of the user; the user can quickly access and deploy the application program without installation and configuration; analyze the user's needs, and combine the subscription information of the user on the SaaS platform to recommend the most suitable SaaS application development components for the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic structural diagram of an enterprise-level application development and data management system based on zero-code SaaS of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the 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. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] Embodiment: As Figure 1As shown in the figure, the present invention provides a technical solution, an enterprise-level application development and data management system based on zero-code SaaS, including: a SaaS platform, a data storage module, a user interaction module, and a data analysis module; the SaaS platform is interconnected with the data storage module, the user interaction module, and the data analysis module, and provides subscribed component services to users through the Internet; the output end of the user interaction module is connected to the input end of the data storage module, and is used to determine the application development requirements of users and recommend components that need to be subscribed to users; the output end of the data storage module is connected to the input end of the data analysis module, and is used to store the component information subscribed by users and the information on the components used by users in the SaaS platform; the data analysis module is connected to the user interaction module, and is used to analyze the matching degree between the components in the SaaS platform and the user requirements, and generate an application development group for users to perform application development.

[0035] The user interaction module further includes an input unit, an output unit, a selection unit, a subscription unit, and an identity authentication unit; the input unit is used to obtain the input keywords and output keywords of users; the output unit is used to present the recommended application development group to users; the selection unit provides an interface for users to select or reject the application development group; the subscription unit provides component subscription services for users after they select the application development group; the identity authentication unit is used to identify the identity of users. The SaaS platform further includes a component library and an application development unit: the component library is used to store components for application development; the application development unit provides an operation interface for users to configure and customize the application according to the component information subscribed by users. The data analysis module further includes a keyword analysis unit, a component analysis unit, an application development group generation unit, and an application development group evaluation unit; the component analysis unit is used to assign keywords to components; the keyword analysis unit is used to determine the matching degree between components and the application development requirements of users; the application development group generation unit generates an application development group according to the input keywords, output keywords, and the matching degree between components and application development requirements; the application development group evaluation unit is used to determine the score value of each application development group.

[0036] Embodiment: The present invention provides a technical solution, an enterprise-level application development and data management method based on zero-code SaaS, including:

[0037] S11, obtain the application development requirement information input by the user, and extract the input keywords and output keywords from the application development requirement information of the user.

[0038] Commonly, the application development requirements of users are to implement function B based on A. For example, product recommendations are made based on consumption records. At this time, the input keyword is the consumption record, and the output keyword is the product recommendation. First, the input component and the output component are selected according to the consumption record and the product recommendation. Then, the execution component is analyzed to find an execution component that can transform the consumption record into a product recommendation. According to the historical usage information of other components, such as the association analysis component, the purchase history analysis component, the trend analysis component, and the preference analysis component, if there are keywords of consumption record or product recommendation, the matching degree between these components and the user requirements can be analyzed.

[0039] S12. Obtain the subscription and development information of components on the SaaS platform, and classify the components into input components, output components, and execution components; assign keywords to the components on the SaaS platform:

[0040] Obtain the historical usage information of components on the SaaS platform, obtain the historical development requirement information of historical users from the historical usage information, and extract historical input keywords and output keywords from the historical development requirement information; add all historical input keywords and output keywords to the keyword set of the components; and calculate the concentration cen of each keyword in the keyword set of the components, cen = num1 / num, where num1 is the number of times the keyword appears in the historical usage information of the component, and num is the total number of times all keywords appear in the historical usage information of the component; if the concentration of the keyword is not less than the set threshold, the keyword is retained in the keyword set of the component; if the concentration of the keyword is less than the set threshold, the keyword is removed from the keyword set of the component; finally, the remaining keywords in the keyword set of the component are the keywords of the component.

[0041] S13. Select input components and output components for the user according to the input keyword and the output keyword; recommend execution components for the user according to the input keyword, the output keyword, the user's subscription information on the SaaS platform, and the development information of the execution components, which specifically includes the following steps:

[0042] S31. According to the input keyword and the output keyword, find all execution components that separately contain the input keyword and separately contain the output keyword, and find all execution components that simultaneously contain the input keyword and the output keyword; for the i-th execution component, if it simultaneously contains the input keyword and the output keyword, go to step S32; if it separately contains the input keyword, go to step S33; if it separately contains the output keyword, go to step S34;

[0043] S32. Let \(X_i\) denote the input keyword random variable of the \(i\)-th execution component, and \(Y_i\) denote the output keyword random variable of the \(i\)-th execution component. For an execution component that contains both input keywords and output keywords, calculate the matching degree between the execution component and the application development requirements through the following formula: \(P_i = P\{X_i = r\cap Y_i = y\} = n(r, y, i) / N(i)\), where \(P_i\) is the matching degree of the \(i\)-th execution component, \(r\) and \(y\) are the input keyword and output keyword respectively, \(n(r, y, i)\) represents the number of times that the input keyword \(r\) and the output keyword \(y\) appear simultaneously in the historical usage information of the \(i\)-th execution component, and \(N(i)\) represents the number of times the \(i\)-th execution component is used; end;

[0044] S33. For the \(i\)-th execution component that only contains the input keyword \(r\), determine the matching degree between the \(i\)-th execution component and the application development requirements through the following formula: The \(i\)-th execution component itself does not include the output keyword \(y\). Calculate the matching degree between the \(i\)-th execution component and the application development requirements by using the usage information of other execution components that contain the input keyword \(r\), and decompose the formula \(P\{X_i = r\cap Y_i = y\}\). Here, \(n\) is the number of execution components that contain the input keyword \(r\), and \(W_1, W_2, \cdots, W_n\) represent the input keyword random variables of the 1st, 2nd, \(\cdots\), \(n\)-th execution components that contain the input keyword \(r\).

[0045] The execution component \(W_j\) represents the \(j\)-th execution component that contains the input keyword \(r\). Calculate the similarity \(sim1(i, j)\) between \(W_j\) and the \(i\)-th execution component, \(sim1(i, j)=(c_i\cap C_{1j}) / (c_i\cup C_{1j})\), where \(c_i\) is the keyword set of the \(i\)-th execution component, \(C_{1j}\) is the keyword set of \(W_j\), \(c_i\cap C_{1j}\) represents the number of repeated keywords between \(W_j\) and the \(i\)-th execution component, and \(c_i\cup C_{1j}\) represents the total number of keywords between \(W_j\) and the \(i\)-th execution component. Calculate the weight of \(W_j\) according to the similarity: \(A_{1j}=sim1(i, j) / \sum sim1(i, j)\);

[0046] Calculate the matching degree \(P_i\) of the \(i\)-th execution component and the application development requirements, where \(N(r, y, j)\) is the number of times that the input keyword \(r\) and the output keyword \(y\) appear simultaneously in the historical usage information of \(W_j\), and \(N(j)\) is the number of times the execution component \(W_j\) is used;

[0047] For W1, W2, and W3, the number of keywords included is 10, and the number of keywords included in the i-th execution component is also 10. The number of keywords identical between W1, W2, and W3 and the i-th execution component is 3, 5, and 9 respectively. Then the similarities between W1, W2, and W3 and the i-th execution component are 3 / 17, 5 / 15, and 9 / 11 respectively. Furthermore, weights are determined based on 3 / 17, 5 / 15, and 9 / 11. When W1 does not contain keyword y, the matching degrees of W1, W2, and W3 with the application development requirements are calculated respectively, and after multiplying by the weights and adding them together, the matching degree of the i-th execution component is obtained.

[0048] S34. For the i-th execution component that solely contains the input keyword y, the matching degree of the i-th execution component with the application development requirements is determined through the following formula: The i-th execution component itself does not include the input keyword r. The matching degree of the i-th execution component with the application development requirements is calculated by leveraging the usage information of other execution components that contain the output keyword y, and the formula P{Xi = r ∩ Yi = y} is decomposed. Here, m is the number of execution components that contain the output keyword y, and V1, V2, …, Vm represent the output keyword random variables of the 1st, 2nd, …, m-th execution components that contain the output keyword y.

[0049] The execution component Vk represents the k-th execution component that contains the output keyword y. The similarity sim2(i, k) between Vk and the i-th execution component is calculated, where sim2(i, k) = (ci ∩ C2k) / (ci ∪ C2k). C2k is the keyword set of Vk, ci ∩ C2k represents the number of repeated keywords between Vk and the i-th execution component, and ci ∪ C2k represents the total number of keywords between Vk and the i-th execution component. The weight of Vk is calculated based on the similarity, A2k = sim2(i, k) / ∑sim2(i, k).

[0050] The matching degree Pi of the i-th execution component with the application development requirements is calculated. In the formula, N(r, y, k) is the number of times the input keyword r and the output keyword y appear simultaneously in the historical usage information of Vk, and N(k) is the number of times the execution component Vk is used.

[0051] Starting from the input keyword r and the output keyword y, the input component and output component of the user requirements are selected. Combining the matching degrees of the execution components with the application development requirements, an application development group is generated. The application development group consists of the input component, output component, and execution component. Combining the component information already subscribed by the user on the SaaS platform, the additional resource information consumed by the user when adopting each application development group is determined.

[0052] Obtain the average matching degree information and the information of additional consumed resources for each application development group. Let AVEu represent the average matching degree of the u-th application development group, and COSTu represent the additional consumed resources of the u-th application development group. Determine the average matching degree of the application development group by calculating the average value of the matching degrees between all execution components in the application development group and the application development requirements. Calculate the sub-evaluation value of each application development group, Fu = H × AVEu + L × COSTu, where H and L are weight values set according to the user's own situation. Sort the sub-evaluation values in descending order and recommend the application development groups to the user for application development.

[0053] S14. The user refers to the recommended results of the execution components and uses the input components, output components and execution components to develop the required applications.

[0054] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. 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 included in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

Claims

1. An enterprise-level application development and data management method based on zero-code SaaS, characterized in that: The following steps are involved: S11, obtaining application development requirement information input by a user, and extracting input keywords and output keywords from the application development requirement information of the user; S12, obtaining subscription and development information of components on the SaaS platform, dividing the components into input components, output components, and execution components; and assigning keywords to the components on the SaaS platform; S13, selecting an input component and an output component for the user according to the input keyword and the output keyword; recommending an execution component to the user according to the input keyword, the output keyword, the user's subscription information on the SaaS platform, and the development information of the execution component; S14, the user refers to the recommendation result of the execution component and uses the input component, the output component and the execution component to develop the required application; In step S12, assigning keywords to components on the SaaS platform further includes the following steps: Obtain the historical usage information of components on the SaaS platform, obtain the historical development demand information of historical users from the historical usage information, and extract the historical input keywords and output keywords from the historical development demand information; add all historical input keywords and output keywords to the keyword set of the component; and calculate the concentration cen of each keyword in the keyword set of the component, cen=num1 / num, where num1 is the number of times the keyword appears in the historical usage information of the component, and num is the total number of times all keywords appear in the historical usage information of the component; if the concentration of the keyword is not less than the set threshold, the keyword is retained in the keyword set of the component; if the concentration of the keyword is less than the set threshold, the keyword is removed from the keyword set of the component; finally, the remaining keywords in the keyword set of the component are the keywords of the component.

2. According to claim 1, a method for enterprise-level application development and data management based on zero-code SaaS, characterized in that: In step S13, the step of recommending an execution component to a user further includes the following steps: S31, according to the input keyword and the output keyword, find all execution components that contain the input keyword alone and the output keyword alone, and find all execution components that contain both the input keyword and the output keyword; for the i-th execution component, if it contains both the input keyword and the output keyword, go to step S32; if it contains only the input keyword, go to step S33; if it contains only the output keyword, go to step S34; S32, let Xi represent the input keyword random variable of the i-th execution component, and Yi represent the output keyword random variable of the i-th execution component; for the execution component containing both input keywords and output keywords, the matching degree between the execution component and the application development requirement is calculated by the following formula: Pi = P{Xi = r∩Yi = y} = n(r, y, i) / N(i), where Pi is the matching degree of the i-th execution component, r and y are the input keyword and output keyword, n(r, y, i) represents the number of times the input keyword r and the output keyword y appear at the same time in the historical usage information of the i-th execution component, and N(i) represents the number of times the i-th execution component is used; end; S33, for the i-th execution component that contains the input keyword r alone, the matching degree between the i-th execution component and the application development requirement is determined by the following formula: The i-th execution component itself does not include the output keyword y. With the help of the usage information of other execution components containing the input keyword r, the matching degree between the i-th execution component and the application development requirements is calculated, and the formula P{Xi=r∩Yi=y} is decomposed; where n is the number of execution components containing the input keyword r, and W1, W2, ..., Wn represent the input keyword random variables of the 1st, 2nd, ..., nth execution components containing the input keyword r; S34, for the i-th execution component that contains the input keyword y alone, the matching degree between the i-th execution component and the application development requirement is determined by the following formula: The i-th execution component itself does not include the input keyword r. With the help of the usage information of other execution components containing the output keyword y, the matching degree between the i-th execution component and the application development requirements is calculated, and the formula P{Xi=r∩Yi=y} is decomposed; where m is the number of execution components containing the output keyword y, and V1, V2, …, Vm represent the output keyword random variables of the 1st, 2nd, …, mth execution components containing the output keyword y.

3. According to claim 2, a method for enterprise-level application development and data management based on zero-code SaaS is characterized in that: In step S33, the following steps are also included: S41, the execution component Wj represents the jth execution component containing the input keyword r, and the similarity sim1(i, j) between Wj and the i-th execution component is calculated, sim1(i, j) = (ci∩C1 j) / (ci∪C1 j), where ci is the keyword set of the i-th execution component, C1 j is the keyword set of Wj, ci∩C1 j represents the number of repeated keywords between Wj and the i-th execution component, and ci∪C1 j represents the number of all keywords between Wj and the i-th execution component; the weight of Wj is calculated according to the similarity, A1 j = sim1(i, j) / ∑sim1(i, j); S42, calculate the matching degree Pi between the i-th execution component and the application development requirement, Where N(r,y,j) is the number of times the input keyword r and the output keyword y appear simultaneously in the historical usage information of Wj, and N(j) is the number of times the execution component Wj is used; In step S34, the following steps are also included: S43, the execution component Vk represents the kth execution component containing the output keyword y, and the similarity sim2(i, k) between Vk and the i-th execution component is calculated, sim2(i, k) = (ci∩C2k) / (ci∪C2k), C2k is the keyword set of Vk, ci∩C2k represents the number of repeated keywords between Vk and the i-th execution component, ci∪C2k represents the number of all keywords between Vk and the i-th execution component; the weight of Vk is calculated according to the similarity, A2k = s im2(i, k) / ∑sim2(i, k); Calculate the matching degree Pi between the i-th execution component and the application development requirements, Where N(r,y,k) is the number of times the input keyword r and the output keyword y appear simultaneously in the historical usage information of Vk, and N(k) is the number of times the execution component Vk is used.

4. According to claim 3, the enterprise-level application development and data management method based on zero-code SaaS is characterized in that: In step S13, the step of recommending an execution component to a user further includes the following steps: S51, taking the input keyword r and the output keyword y as the starting point, selecting the input component and the output component required by the user; combining the matching degree between the execution component and the application development requirement, generating an application development group, the application development group consisting of the input component, the output component and the execution component; S52, combining the component information subscribed by the user on the SaaS platform, determining the additional resource information consumed when the user adopts each application development group.

5. According to claim 4, a method for enterprise-level application development and data management based on zero-code SaaS is characterized in that: In step S13, the step of recommending an execution component to a user further includes the following steps: The average matching degree information and additional resource consumption information of each application development group are obtained, and AVEu is used to represent the average matching degree of the u-th application development group, and COSTu is used to represent the additional resource consumption of the u-th application development group. The average matching degree of the application development group is determined by calculating the average matching degree of all execution components in the application development group with the application development requirements. The score valuation of each application development group is calculated, Fu = H × AVEu + L × COSTu; where H and L are weights, which are set according to the user's own situation. The score valuations are arranged in descending order, and the application development groups are recommended to users for application development.

6. An enterprise-level application development and data management system based on zero-code SaaS, used to implement an enterprise-level application development and data management method based on zero-code SaaS as claimed in claim 1, characterized in that: include: SaaS platform, data storage module, user interaction module and data analysis module; The SaaS platform is interconnected with the data storage module, the user interaction module and the data analysis module to provide subscribed component services to users through the Internet; the output end of the user interaction module is connected to the input end of the data storage module to determine the user's application development needs and recommend components that need to be subscribed to the user; the output end of the data storage module is connected to the input end of the data analysis module to store the component information subscribed by the user and the information on the components in the SaaS platform being used by the user; the data analysis module is connected to the user interaction module to analyze the matching degree between the components in the SaaS platform and the user needs, and generate an application development group to provide to the user for application development.

7. The enterprise-level application development and data management system based on zero-code SaaS according to claim 6, characterized in that: The user interaction module further includes an input unit, an output unit, a selection unit, a subscription unit and an identity authentication unit; the input unit is used to obtain input keywords and output keywords of the user; the output unit is used to present the recommended application development group to the user; The selection unit provides an interface for the user to select or reject the application development group; The subscription unit provides the user with component subscription service after the user selects an application development group; the identity authentication unit is used to identify the user's identity.

8. The enterprise-level application development and data management system based on zero-code SaaS according to claim 7, characterized in that: The SaaS platform also includes a component library and an application development unit: the component library is used to store components for application development; The application development unit provides an operation interface to the user to configure and customize the application according to the component information subscribed by the user.

9. The enterprise-level application development and data management system based on zero-code SaaS according to claim 8, characterized in that: The data analysis module further includes a keyword analysis unit, a component analysis unit, an application development group generation unit, and an application development group evaluation unit; the component analysis unit is used to assign keywords to components; the keyword analysis unit is used to determine the matching degree between components and the user's application development requirements; The application development group generating unit generates an application development group according to the matching degree between the input keywords, the output keywords and the components and the application development requirements; the application development group evaluating unit is used to determine the score value of each application development group.

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