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

Abstract

The invention discloses an enterprise-level application development and data management system and method based on zero code SaaS, and relates to the technical field, application development demand information input by a user is obtained, and input keywords and output keywords are extracted from the application development demand information of the user; acquiring subscription and development information of components on the SaaS platform; giving keywords to the components on the SaaS platform; selecting an input component and an output component for a user; recommending an execution component to the user; the user uses the input component, the output component and the execution component to develop required applications by referring to a recommendation result of the execution component; the user does not need to purchase and maintain software, resource consumption of the user is reduced, and maintenance burden of the user is reduced; the user can quickly access and deploy the application program without installation and configuration; and analyzing the requirements of the user, and recommending an SaaS application development component which is most practical to the user in combination with subscription information of the user on the SaaS platform.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular 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 applications through the Internet. Users do not need to purchase or install software, but subscribe to and use software services through the Internet. This model provides enterprises with flexible, scalable and efficient solutions, while also reducing costs and complexity 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 updates, upgrades and security assurance. Using the tools and modules provided by the SaaS platform for application design and development allows enterprises to quickly and efficiently build and deploy enterprise-level applications. To this end, how to recommend SaaS application development components to enterprises based on their application development needs and their 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 object, the present invention provides the following technical solution: an enterprise-level application development and data management method based on zero-code SaaS, comprising:

[0005] 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;

[0006] S12, obtain the subscription and development information of components on the SaaS platform, divide the components into input components, output components and execution components; assign keywords to the components on the SaaS platform; the development information of components on the SaaS platform does not need to know the specific details, only the general development purpose of the components needs to be known through user authorization, so as to protect user privacy and prevent the components from being used incorrectly;

[0007] 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;

[0008] 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.

[0009] In step S12, assigning 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 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.

[0011] In step S13, the step of recommending an execution component to a user further includes the following steps:

[0012] 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;

[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 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;

[0014] 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;

[0015] 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.

[0016] The needs of users are reflected through input keywords and output keywords. Execution components that include both keywords can be recommended to users, and users can decide whether to adopt them. For execution components that only include one keyword, the matching degree is determined by using the information of other execution components that include 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. For the remaining 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 at present may be: too high resource consumption, small number of subscribers; the component was generated a short time ago, and the popularity is not high, etc. When the matching degree is determined by the information of other execution components that include the same keyword, the weight of the information of other execution components is determined according to the similarity. The same is true for the execution component that includes 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 also included:

[0018] 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);

[0019] 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.

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

[0021] 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 = sim2(i, k) / ∑sim2(i, k);

[0022] 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.

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

[0024] 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;

[0025] 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.

[0026] In step S13, the step of recommending an execution component to a user further includes the following steps:

[0027] 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.

[0028] Typically, users only subscribe to some components on SaaS, because when recommending application development components to users, it is necessary to consider the resource consumption caused by additional subscription components.

[0029] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an enterprise-level application development and data management system based on zero-code SaaS, comprising: 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 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.

[0030] The user interaction module also includes an input unit, an output unit, a selection unit, a subscription unit and an identity verification unit; the input unit is used to obtain the user's input keywords and output keywords; the output unit is used to present the recommended application development group to the user; the selection unit provides the user with an interface for selecting or rejecting the application development group; the subscription unit provides the user with a component subscription service after the user selects the application development group; the identity verification unit is used to identify the user's identity. 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 the user with an operation interface to configure and customize the application according to the component information subscribed by the user. The data analysis module also 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 generation unit generates application development groups 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.

[0031] Compared with the prior art, the beneficial effects of the present invention are: users do not need to purchase and maintain software, which reduces users' resource consumption and maintenance burden; users can quickly access and deploy applications without installation and configuration; the present invention analyzes user needs and recommends SaaS application development components that best suit their actual needs based on the user's subscription information on the SaaS platform. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Example: Figure 1As shown, the present invention provides a technical solution, an enterprise-level application development and data management system based on zero-code SaaS, comprising: 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 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, so as to determine the application development needs of the user 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, so as 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, so as 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.

[0035] The user interaction module also includes an input unit, an output unit, a selection unit, a subscription unit and an identity verification unit; the input unit is used to obtain the user's input keywords and output keywords; the output unit is used to present the recommended application development group to the user; the selection unit provides the user with an interface for selecting or rejecting the application development group; the subscription unit provides the user with a component subscription service after the user selects the application development group; the identity verification unit is used to identify the user's identity. 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 the user with an operation interface to configure and customize the application according to the component information subscribed by the user. The data analysis module also 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 generation unit generates application development groups 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, comprising:

[0037] 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.

[0038] Commonly, the user's application development needs are to implement function B based on A, such as recommending products based on consumption records. In this case, the input keyword is the consumption record, and the output keyword is the product recommendation. First, select the input component and output component based on the consumption record and product recommendation, then analyze the execution component to find the execution component that can convert the consumption record into product recommendation. Based on the historical usage information of other components, such as the association analysis component, purchase history analysis component, trend analysis component, and preference analysis component, if there are keyword consumption records or product recommendations, the matching degree between these components and user needs can be analyzed.

[0039] S12, obtain the subscription and development information of the components on the SaaS platform, divide 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 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.

[0041] 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, specifically including the following steps:

[0042] 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;

[0043] 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;

[0044] 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;

[0045] The execution component Wj represents the jth execution component containing the input keyword r. The similarity sim1(i, j) between Wj and the i-th execution component is calculated. s im1(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 based on the similarity, A1 j = s im1(i, j) / ∑ s im1(i, j);

[0046] Calculate the matching degree Pi between the i-th execution component and the application development requirements, 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;

[0047] For W1, W2 and W3, the number of keywords included is 10, the number of keywords included in the i-th execution component is also 10, the number of keywords that W1, W2 and W3 have in common with the i-th execution component are 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, and the weights are determined based on 3 / 17, 5 / 15 and 9 / 11; when W1 does not contain the keyword y at the same time, the matching degree of W1, W2 and W3 with the application development requirements is calculated respectively, multiplied by the weight and then added to obtain the matching degree of the i-th execution component.

[0048] 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;

[0049] 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 = sim2(i, k) / ∑sim2(i, k);

[0050] 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.

[0051] Taking the input keyword r and the output keyword y as the starting point, select the input components and output components required by the user; combine the matching degree between the execution component and the application development requirements to generate an application development group, which consists of input components, output components and execution components; combine the component information subscribed by the user on the SaaS platform to determine the additional resource information consumed when the user adopts each application development group.

[0052] 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.

[0053] 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.

[0054] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

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.

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 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.

3. 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.

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 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 = sim2(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.

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: 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.

6. The enterprise-level application development and data management method based on zero-code SaaS according to claim 5, 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.

7. An enterprise-level application development and data management system based on zero-code SaaS, 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.

8. The enterprise-level application development and data management system based on zero-code SaaS according to claim 7, 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.

9. The enterprise-level application development and data management system based on zero-code SaaS according to claim 8, 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.

10. The enterprise-level application development and data management system based on zero-code SaaS according to claim 9, 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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