Interactive Information Processing Method, Apparatus and Computer Device

Abstract

The present application provides an interactive information processing method, apparatus, and computer device. The present application uses the relevant data of each interactive form under each published application to pre-generate API relationship topology data that can represent the association relationship and association factors between the application programming interfaces (APIs) bound to different published interactive forms. In this way, when an API processing request for a target API corresponding to a to-be-processed interactive form for a target application is obtained and the API processing request is responded to, the API relationship topology data can be directly queried, and the association relationship and association factors between the APIs are comprehensively considered, so as to quickly and accurately obtain the query result of the target API and perform a preset operation to meet the business processing requirements. Compared with the processing method of directly querying the target API from a large number of APIs based on API keywords, the query efficiency and accuracy of the target API are improved.

Description

Technical Field

[0001] This application mainly relates to the field of computer technology, and more specifically, to an interactive information processing method, apparatus, and computer device. Background Art

[0002] Low-code is a method with less programming effort but can quickly design and develop software application programs. It can rely on libraries, APIs (Application Program Interfaces), and third-party infrastructures, and directly use visual modeling on a drag-and-drop interface to assemble and configure applications, improving application development efficiency and reliability, reducing development costs, and facilitating later maintenance.

[0003] Among them, during the design process of a low-code platform, APIs are searched through keywords and bound to the corresponding interactive forms at the front end to achieve application interaction capabilities. However, in the case of a large number of APIs at the back end, it is often difficult to quickly and accurately search for the required APIs, reducing the efficiency and reliability of application design and development. Summary of the Invention

[0004] In view of this, this application proposes an interactive information processing method, which includes:

[0005] Obtain an API processing request for a target application programming interface (API) corresponding to a to-be-processed interactive form for a target application;

[0006] Respond to the API processing request and query the generated API relationship topology data; wherein, the API relationship topology data can characterize the association relationships and association factors between the APIs bound to different published interactive forms;

[0007] Execute a preset operation according to the query result of the target API.

[0008] Optionally, the method for generating the API relationship topology data includes:

[0009] Obtain the relevant data of the interactive forms of the published applications;

[0010] Perform a correlation analysis on the relevant data of the interactive forms to determine the association relationships and association factors between the different APIs bound to each interactive form;

[0011] Generate API relationship topology data according to the association relationships and association factors between the different APIs.

[0012] Optionally, the obtaining of the relevant data of the interactive forms of the published applications includes:

[0013] Obtain the configuration data of the interactive forms of the published application and the parameter call data generated by accessing the interactive forms;

[0014] Perform a correlation analysis on the relevant data of the interactive forms to determine the association relationships and association factors between different APIs bound to each interactive form, including:

[0015] Perform a correlation analysis on the configuration data of the interactive forms to determine the association relationships between different APIs bound to each interactive form;

[0016] Perform a correlation analysis on the parameter call data to determine the association factors between different APIs having the association relationships.

[0017] Optionally, the obtaining the configuration data of the interactive forms of the published application and the parameter call data generated by accessing the interactive forms includes:

[0018] Obtain the binding relationships between different interactive forms and different APIs of the published application, and the API parameters corresponding to each of the different APIs; the API parameters characterize the output information in the interactive forms having a binding relationship with the corresponding APIs;

[0019] Obtain the API parameter call data for an interactive form during the process of responding to an access request for any interactive form of the published application.

[0020] Optionally, the performing a correlation analysis on the configuration data of the interactive forms to determine the association relationships between different APIs bound to each interactive form includes:

[0021] Based on the API parameters of each API, the bound interactive forms, and the category of the published application to which the interactive form belongs, statistically calculate the first co-occurrence probability between any two APIs;

[0022] Based on the first co-occurrence probability, obtain the first confidence level for the association relationship between the corresponding two APIs;

[0023] If the first confidence level is within the first confidence interval, determine that there is an association relationship between the corresponding two APIs.

[0024] Optionally, the performing a correlation analysis on the parameter call data to determine the association factors between different APIs having the association relationships includes:

[0025] Using the API parameter call data between any two APIs having the association relationships, statistically calculate the second co-occurrence probability of each API parameter in different API calls;

[0026] Obtain a second confidence level that the respective API parameters make the corresponding two APIs have an association relationship according to the second co-occurrence probability;

[0027] If the second confidence level is within the second confidence interval, determine the corresponding API parameter as an association factor that makes the corresponding two APIs have an association relationship.

[0028] Optionally, the correlation analysis of the relevant data of the interaction form to determine the association relationship and association factors between different APIs bound to each interaction form includes:

[0029] Invoke an API correlation analysis model; the API correlation analysis model is constructed based on a conditional probability algorithm;

[0030] Input the relevant data of the interaction form into the API correlation analysis model to obtain a list of APIs associated with the APIs bound to the interaction form of the published application, and the association factors between the API and any API in the list of APIs associated with itself.

[0031] Optionally, the response to the API processing request to query the generated API relationship topology data includes:

[0032] Obtain the information to be queried carried by the API processing request; the information to be queried is determined based on the target API parameters of the target API;

[0033] Query the generated API relationship topology data to obtain multiple candidate APIs that match the information to be queried, as well as associated APIs and corresponding candidate association factors that have an association relationship with the candidate APIs;

[0034] Screen out the target API from the multiple candidate APIs according to the API parameters of the associated API and the corresponding candidate association factors;

[0035] The execution of the preset operation according to the query result of the target API includes:

[0036] Bind the identified target API to the interaction form to be processed;

[0037] Update the API relationship topology data according to the binding relationship between the interaction form to be processed and the target API.

[0038] This application also proposes an interaction information processing device, and the device includes:

[0039] An API processing request acquisition module, configured to acquire an API processing request for a target application programming interface (API) corresponding to a to-be-processed interaction form for a target application;

[0040] A target API query module, configured to respond to the API processing request and query generated API relationship topology data; wherein, the API relationship topology data can characterize the association relationship and association factors between APIs bound to different published interaction forms;

[0041] A processing module, configured to perform a preset operation according to the query result of the target API.

[0042] This application also provides a computer device, which includes: at least one communication interface, at least one memory, and at least one processor, wherein:

[0043] The memory is used to store a program of the interaction information processing method as described above;

[0044] The processor is configured to load and execute the program in the memory to implement the interaction information processing method as described above.

[0045] This application also provides a computer-readable storage medium, on which computer instructions are stored, and the processor loads and executes the computer instructions to implement the interaction information processing method as described above.

[0046] It can be seen that this application provides an interaction information processing method, device, and computer device. This application uses the relevant data of each interaction form under each published application to pre-generate API relationship topology data that can characterize the association relationship and association factors between APIs bound to different published interaction forms. In this way, when an API processing request for a target API corresponding to a to-be-processed interaction form for a target application is obtained and the API processing request is responded to, the API relationship topology data can be directly queried, and the association relationship and association factors between each API can be comprehensively considered, so as to quickly and accurately obtain the query result of the target API and perform a preset operation to meet the business processing requirements. Compared with the method of directly querying the target API from a large number of APIs based on API keywords, the query efficiency and accuracy of the target API are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0048] Figure 1 It is a schematic flowchart of an optional example of the interaction information processing method proposed in this application;

[0049] Figure 2 It is a schematic flowchart of another optional example of the interaction information processing method proposed in this application;

[0050] Figure 3 It is a schematic diagram of an optional representation of the API relationship topology data generated in the interaction information processing method proposed in this application;

[0051] Figure 4 It is a schematic flowchart of another optional example of the interaction information processing method proposed in this application;

[0052] Figure 5 It is a schematic flowchart of another optional example of the interaction information processing method proposed in this application;

[0053] Figure 6 It is a schematic flowchart of another optional example of the interaction information processing method proposed in this application;

[0054] Figure 7 It is a schematic structural diagram of an optional example of the interaction information processing device proposed in this application;

[0055] Figure 8 It is a schematic structural diagram of another optional example of the interaction information processing device proposed in this application;

[0056] Figure 9 It is a schematic structural diagram of another optional example of the interaction information processing device proposed in this application;

[0057] Figure 10 It is a schematic hardware structure diagram of an optional example of a computer device applicable to the interaction information processing method proposed in this application. Detailed implementation manners

[0058] Currently, the development of applications usually includes front-end development and back-end development. Front-end development can be the graphic design of interactive forms in the front-end pages of applications, and back-end development can be the code design for implementing the business logic that supports the front-end interactive forms. To achieve the docking between the back-end and the front-end, back-end developers can expose the back-end program code as an API (Application Program Interface), and front-end developers can bind the designed interactive forms to the corresponding APIs to enable the interactive forms to have interactive capabilities.

[0059] Among them, to simplify development, a large number of pre-developed and encapsulated components in the low-code platform can be utilized to achieve application development. For the design of an interactive form, a front-end developer can, according to a certain logical relationship or design layout, complete the design of the interactive form by dragging relevant components required for the interactive form, such as input boxes, edit boxes, function components such as modify / delete / details, etc., so as to reduce the workload of developers writing code, shorten the design time of the interactive form, and improve development efficiency and reliability. A back-end developer can also, on the low-code platform, bind the interactive form to one or more corresponding APIs by dragging components. In this way, during the use of the interactive form, the required business can be quickly realized by calling the APIs bound to the triggered components. The implementation process is not elaborated in this application.

[0060] Thus, to achieve the interaction ability of the interactive form, it is necessary to bind one or more required APIs (which can be denoted as target APIs for convenience of description) to the designed interactive form. This requires first querying the target APIs required by the interactive form from a large number of pre-developed API components on the low-code platform. However, the number of pre-developed APIs on the low-code platform is often relatively large. If the relevant information of the provided target APIs is not sufficient, it is very difficult to quickly and accurately query the target APIs.

[0061] To improve the above problems, it is proposed to classify and manage a large amount of API information on the low-code platform to generate an API directory with a preset layout. In this way, through this API directory, the target APIs required by the interactive form to be processed can be queried and located, and the query efficiency can be improved by narrowing the API query range. However, the maintenance of the API directory information and the API information depends on the personal cognition and experience of the staff, which inevitably leads to inaccurate or incorrect API classification in the API directory, interfering with the subsequent query and location of the target APIs.

[0062] In response to this, this application proposes to generate API relationship topology data representing the association relationship and the associated factors based on the association relationship between the APIs bound to different published interactive forms and the associated factors that cause the association relationship between different APIs, such as one or more field information in the corresponding interactive form, etc. In this way, in the application development scenario of the low-code platform, when it is necessary to determine the APIs corresponding to the newly designed interactive form, or in scenarios such as optimizing the applications already developed on the low-code platform, when it is necessary to determine the APIs corresponding to the interactive form to be optimized, etc., after the computer device obtains the corresponding API processing request, during the process of responding to the API processing request, it can directly query the generated API relationship topology data, and combine the association relationship and the associated factors between different APIs to quickly and accurately locate the target APIs and perform preset operations.

[0063] Moreover, since the generation of API relationship topology data is based on the objective analysis of data to determine the association relationships and association factors between different APIs, it does not need to rely on experienced developers for maintenance, reducing the maintenance cost, ensuring the reliability and accuracy of API relationship topology data, thereby improving the accuracy of target API query and positioning, and further reducing the application design and development efficiency.

[0064] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0065] Refer to Figure 1 , which is a schematic flowchart of an optional example of the interaction information processing method proposed in this application. This method can be applied to computer devices. In the actual application of this application, the computer device may include a terminal device and / or a service device. Among them, the terminal device may include, but is not limited to, electronic devices such as smart phones, tablet computers, wearable devices, augmented reality (AR) devices, virtual reality (VR) devices, in-vehicle devices, robots, intelligent medical devices, intelligent transportation devices, and desktop computers; the service device may be an independent physical server, or a server cluster composed of multiple physical servers, or a cloud server capable of implementing cloud computing, etc. The service device can realize data communication with the terminal device through a wired network or a wireless network to meet the data transmission requirements. The implementation manner of data transmission is not limited in this application and can be determined according to the situation.

[0066] Based on this, taking the service device executing this method as an example for illustration, as Figure 1 shown, the interaction information processing method proposed in this embodiment may include, but is not limited to, the following steps:

[0067] Step S11, obtain an API processing request for a target API corresponding to a to-be-processed interaction form for a target application;

[0068] In an embodiment of the present application, the target application can be any application developed or being developed by a low-code platform. In the target application development scenario, for any interactive form (denoted as the to-be-processed interactive form) in the target application designed for the front end, at least one API needs to be bound to implement the application interaction capability of this interactive form. In this case, the front-end developer can log in to the low-code platform through the client and initiate an API processing request for the target API corresponding to the to-be-processed interactive form to request to query which one or more APIs the target API is.

[0069] It should be noted that for each API pre-developed on the low-code platform, it can be bound to the interactive form of the front end of one application developed by the low-code platform, or can be bound to the interactive forms of the front ends of multiple applications developed by the low-code platform, or can also be bound to different interactive forms of the same application front end, depending on the situation. For the scenario where any interactive form developed for any application front end is bound to at least one required API, the query process for this API is similar, and the embodiments of the present application will not elaborate one by one.

[0070] In addition, it can be understood that in other scenarios such as the optimization of the interactive form of an application, when it is necessary to query the optimization API to which the interactive form (such as the interactive form to be optimized or processed, uniformly denoted as the to-be-processed interactive form) will be bound, this optimization API is denoted as the target API, and the client can generate an API processing request for this target API and send this API processing request to the computer device so that the computer device can quickly and accurately query the required target API on the low-code platform according to the interactive information processing method proposed in the present application.

[0071] It can be seen that the request content of the API processing request generated by the client can be determined according to the actual application requirements of the corresponding application scenario, and usually can include the relevant information of the target API for request processing, so that the computer device can perform subsequent accurate query based on the request content. The present application does not limit the generation method of the API processing request and the request content it contains.

[0072] Step S12, in response to the API processing request, query the generated API relationship topology data;

[0073] Continuing from the above description of the API processing request, the computer device parses the API processing request to determine relevant information about the target API corresponding to the to-be-query interactive form provided by the client, such as the target API information and / or keywords in the to-be-query interactive form information. After that, based on this relevant information, a query is performed on the generated API relationship topology data. Since this API relationship topology data can represent the association relationships and associated factors between the APIs bound to different published interactive forms. Therefore, the computer device can query the API relationship topology data on the low-code platform according to the request content carried in the API processing request, and can obtain multiple APIs that match the request content. In this way, the association relationships and associated factors between these multiple APIs can be analyzed to accurately and quickly locate the requested target API. The query process is not described in detail in this application.

[0074] Step S13, according to the query result of the queried target API, perform a preset operation.

[0075] In the embodiment of this application, for the query result of the above-mentioned queried target API, it may include information such as the name of the target API and API parameters, so as to determine which one or more APIs the target API is. After that, a preset operation can be performed on the target API, such as binding the target API to the to-be-query interactive form, or outputting the queried target API information for developers to optimize and update it, etc. The implementation method of the preset operation is not limited in this application and can be determined according to the situation.

[0076] In summary, this application uses the API topology relationships such as the association relationships and associated factors between the APIs bound to the interactive forms of the published applications to supplement the description of each API information, so that the portraits of the pre-developed APIs on the low-code platform are clearer. Combining the API topology relationships, it is easier for API users to accurately identify the required target API, thereby meeting the application requirements. Compared with the API query method based on keywords, the query efficiency and accuracy of the target API are improved, thereby improving the application development efficiency and reliability, and reducing the labor cost.

[0077] Refer to Figure 2 , which is a schematic flowchart of another optional example of the interactive information processing method proposed in this application. This embodiment can be a description of an optional refined implementation method of the generation method of the API relationship topology data in the interactive information processing method described in the above embodiment, but is not limited to this refined implementation method described in this embodiment. For other implementation steps on how to use this API relationship topology data to implement target API query, reference can be made to the corresponding part of the above embodiment, and this embodiment will not be elaborated. Such as Figure 2As shown in the figure, the method for generating API relationship topology data proposed in this embodiment may include:

[0078] Step S21: Obtain the relevant data of the interactive forms of the published applications;

[0079] In the embodiments of the present application, the published application may be any application developed using a low-code platform. During the application development process, at least one interactive form of the application can be designed, the required APIs can be bound to each interactive form, and after the application passes the test, the application is published so that users can use the application, that is, use the interactive forms of the application to meet the users' corresponding business usage requirements.

[0080] In the above process, the relevant configuration data of the APIs bound to each interactive form of the published application, as well as the API parameters actually used when the user triggers the interactive form and calls the API bound to the interactive form, that is, information such as the data of each field presented by the output interactive form, can be obtained and used as the relevant data of the interactive form to realize the correlation analysis of the interactive form. It should be noted that the content of the relevant data of the interactive form obtained by the computer device includes but is not limited to the above information listed in the present application, and can be flexibly determined according to actual needs, and the embodiments of the present application do not list them one by one here.

[0081] In addition, the present application does not limit the application type of the published application and the source of the relevant data of the interactive forms it has, etc., which can be determined according to the situation.

[0082] Step S22: Perform a correlation analysis on the relevant data of the interactive forms to determine the association relationships and association factors between different APIs bound to each interactive form;

[0083] The correlation analysis of data can also be called association mining, which is to find the correlation or relevance between the relevant data of different interactive forms, such as a certain combination of data that frequently appears in different interactive forms; if one type of data coexists with another type or multiple types of data, etc., thereby describing the commonality of a certain type of data in the interactive form and determining the degree of association between the corresponding interactive forms. The association analysis algorithm used in the present application to implement the correlation analysis in step S22 is not limited, and can be flexibly selected and adapted according to the data type and characteristics, etc. The implementation process is not described in detail in the embodiments of the present application.

[0084] Based on this, since the configuration data of different interactive forms of the same application that have been published, and the interactive forms of different applications respectively, contain the APIs bound to each interactive form, as well as various API parameters bound to each interactive form, etc. According to the above-mentioned correlation analysis method, analyzing the configuration data of each interactive form can determine the same or multiple API parameters existing between different interactive forms, the frequency of each API parameter appearing in different interactive forms, etc. After that, based on these common parameters obtained from the analysis, it can be determined whether there is a correlation between the APIs bound to the corresponding two interactive forms; at the same time, during the use of the interactive form, a correlation analysis can be performed on the actually used API parameters to determine which API parameters cause the correlation between the different APIs bound to the corresponding interactive form, that is, to determine the correlation factors that cause the correlation between different APIs.

[0085] It should be understood that for the interactive forms of the same category in different applications, for the APIs bound to different interactive forms under the same or different applications, the correlation factors that cause the correlation between different APIs may be different and can be determined according to the situation. The present application does not limit the content of each correlation factor.

[0086] Step S23, generate API relationship topology data according to the correlation between different APIs and the correlation factors.

[0087] The present application does not limit the representation method of the API relationship topology data and can be determined according to actual needs. In a possible implementation manner, according to the above analysis, after determining the APIs with a correlation relationship and the correlation factors that cause the correlation between each API, these APIs can be used as the relationship nodes of the relationship topology graph, and the connection lines between different relationship nodes indicate that there is a correlation between the corresponding APIs, and the correlation factors that cause this correlation can be configured on this connection line, such as Figure 3 a schematic diagram of an optional representation method of the API relationship topology data shown. For example, for APIs such as API1, API2, API3, API4 developed on a low-code platform, each API is configured with a corresponding address id and API parameters ( Figure 3 only two parameters are given as an example for illustration, but it is not limited to Figure 3 the number of APIs shown and the number of parameters of each API).

[0088] According to the correlation analysis method described above, determine the correlation relationship and correlation factors between these APIs. For example, there is a correlation relationship between API1 and API2 due to the correlation factor of parameter 1, there is a correlation relationship between API1 and API4 due to the correlation factor of parameter 2, there is a correlation relationship between API2 and API3 due to the correlation factor of parameter 4, etc. After that, the following can be generated accordingly, such asFigure 3 API relationship topology data of the shown relationship topology structure, but not limited to Figure 3 the shown relationship topology structure.

[0089] It can be seen that by representing the association relationships and association factors between different APIs through the API relationship topology structure, the associations between a large number of pre-developed APIs on the low-code platform become more organized. In this way, when it is necessary to query the target API required for a to-be-processed interaction form, after the developer provides relevant information about the target API and / or the to-be-processed interaction form, the computer device can match it with the API parameters of each API in the API relationship topology data, and combine the matching results and the association relationships and relationship factors between different APIs to locate the target API. The implementation process is not described in detail in this application.

[0090] Referring to Figure 4 , which is a schematic flowchart of another optional example of the interaction information processing method proposed in this application. This embodiment can be an optional refined implementation manner of the method for generating the API relationship topology data described above, but not limited to this refined implementation manner described in this embodiment. As Figure 4 shown, the method may include:

[0091] Step S41, obtaining the binding relationships between different interaction forms and different APIs of the published application, and the API parameters corresponding to different APIs respectively;

[0092] Step S42, obtaining the API parameter call data for the interaction form during the process of responding to an access request for any interaction form of the published application;

[0093] Combining Figure 5 the schematic flowchart of the interaction information processing method shown, and the relevant descriptions of the technical solution of this application in the above embodiments, after the front-end developer completes the design and construction of the interaction form of the application, according to the design content of the interaction form, at least one required API is bound to the interaction form. For example, in the case where a certain list interaction form contains components or events such as modification, deletion, and details, the list API of the list interaction form can be bound to the modification API, deletion API, and details API, and combined with information such as the address id and API parameters of these APIs themselves, the configuration data of the list interaction form is formed. In this way, the API binding of each interaction form designed for the application is completed. After the application development and testing are completed, the application can be published to the corresponding application platform. The implementation process of the application development and testing is not described in detail in this application.

[0094] For a published application, after the user downloads and installs it or logs in online, when entering any interactive form under the application and triggering any component presented in the interactive form, the API parameters corresponding to the component bound to the interactive form can be called to implement the business function of the component and output the corresponding business data. At this time, the business data can be output in the form of an interactive form and the interactive form can be accessed continuously. During this access process, corresponding log data can be generated, including the call data of API parameters during the operation of the interactive form, etc. The present application does not limit the content and recording method of the log data.

[0095] Based on this, when it is necessary to generate API relationship topology data on a low-code platform, the configuration data of the interactive forms of the published applications and the parameter call data generated by accessing the interactive forms can be obtained. As analyzed above, the configuration data is determined during the application development stage when designing the corresponding interactive forms; the parameter call data can refer to the API parameter call data obtained by operating the interactive forms under the published applications during their operation. The present application does not limit the data content of the above configuration data and parameter call data, which can be determined according to application requirements.

[0096] Step S43: According to the respective API parameters of the obtained APIs and the interactive form bound to the API, and the category of the published application to which the interactive form belongs, calculate the first co-occurrence probability between any two APIs.

[0097] In the actual application of the present application, in a manner that follows but is not limited to the above description, after sampling the configuration data of the interactive forms under the published applications, the correlation analysis can be performed on the sampled configuration data of the interactive forms to determine the association relationship between different APIs bound to each interactive form. Optionally, for a large amount of collected configuration data of interactive forms, the correlation analysis can be performed based on the API parameters in the configuration data to calculate the associated API list of any one API, that is, the various APIs that have an association relationship with any one API, that is, to determine the various APIs associated with each API itself. The present application does not limit the correlation analysis algorithm used to obtain the associated API list of each API, nor does it limit the implementation method of how to implement the correlation analysis of the above configuration data.

[0098] In some embodiments proposed in this application, in order to accurately determine whether there is an association relationship between different APIs on a low-code platform, this embodiment proposes to use a probability statistical method, such as the Bayesian conditional probability statistical method, etc., to analyze the configuration data of different interaction forms obtained, and determine the co-occurrence probability of any two APIs (for the sake of distinction, this application refers to the co-occurrence probability here as the first co-occurrence probability), such as the probability that these two APIs exist simultaneously in multiple APIs bound to the same interaction form, the probability that these two APIs exist simultaneously in the APIs bound to different interaction forms of the same published application, the probability that these two APIs exist simultaneously in the APIs bound to the same or different interaction forms of the same category of published applications, etc. This application does not limit the statistical implementation method of the co-occurrence probability.

[0099] Based on the above analysis, in order to obtain the first co-occurrence probability between two APIs, the configuration data of each interaction form obtained above may include information such as the binding relationship between different interaction forms and different APIs, the API parameters corresponding to different APIs respectively, and the category of the published application to which the interaction form belongs. And it can be understood that in the above data sampling stage, the more the number of published applications sampled and the richer the categories, the more the number of published interaction forms sampled and the more diverse the types, according to the probability statistical method proposed in this embodiment, the more reliable the obtained co-occurrence probability value is, making the calculation result of the API association relationship more reliable and accurate, thereby improving the reliability and accuracy of the subsequent obtained API relationship topology data. However, this application does not limit the number and category of the published applications sampled and their respective interaction forms, which can be determined according to the situation.

[0100] Regarding the above co-occurrence probability, it can refer to the probability that two APIs appear together. In order to improve the statistical accuracy, a moving window of an appropriate size can be preset, and thus determine whether other APIs appear near an API (that is, a range formed by radiating around the API to the radius length of the moving window). If other APIs appear, it can be considered that this API co-occurs with each of the other APIs that appear. Accordingly, the co-occurrence times of every two APIs in the obtained configuration data are counted, and then the first co-occurrence probability corresponding to the two APIs is calculated. In this statistical process, the coincidence degree between the API parameters respectively possessed by the APIs can also be combined to determine the first co-occurrence probability of the two APIs, not limited to the co-occurrence statistics of two APIs with exactly the same API information, and the implementation process is not described in detail in this application.

[0101] It should be noted that this application does not limit the calculation method of the co-occurrence probability. According to needs, appropriate probability statistical algorithms can be used to implement it, or a co-occurrence probability statistical model can be pre-trained. In this way, the obtained configuration data can be directly input or input into the co-occurrence probability statistical model after preprocessing, and the first co-occurrence probability of every two APIs can be output. The implementation process is not described in detail in this application.

[0102] Step S44: Obtain the first confidence level indicating an association relationship between the corresponding two APIs based on the first co-occurrence probability.

[0103] Step S45: If the first confidence level is within the first confidence interval, determine that there is an association relationship between the corresponding two APIs.

[0104] In the embodiments of this application, if the first co-occurrence probability between two APIs is higher, it may be that these two APIs appear in the same published application at the same time, and / or the probability of binding to the same interaction form is higher, etc. It can be considered that the degree of association between these two APIs is higher, and the probability that they have an association relationship is higher. This application can use the confidence level to represent the credibility / probability that the association relationship between two APIs holds. In this case, it means that the first confidence level indicating an association relationship between these two APIs is higher. If it reaches the preset first confidence interval indicating that the association relationship between two APIs holds, it can be considered that there is an association relationship between these two APIs, that is, the association relationship between these two APIs holds.

[0105] Among them, the first confidence interval can represent the range of credibility of the association relationship between two APIs, which can be determined by analyzing historical data. This application does not limit the numerical value of the first confidence interval and its determination method.

[0106] Combined with the above analysis, in the embodiments of this application, there is a positive correlation between the first co-occurrence probability of two APIs and the first confidence level indicating an association relationship between them. For example, the greater the first co-occurrence probability, the higher the corresponding first confidence level. However, this application does not limit the conversion rule between the first co-occurrence probability and the first confidence level, that is, the implementation method of how to determine the first confidence level based on the first co-occurrence probability is not limited. Based on this, for the first co-occurrence probability of every two APIs obtained, the first co-occurrence probability can be converted according to the preset conversion rule between the first co-occurrence probability and the first confidence level to obtain the corresponding first confidence level.

[0107] After that, the first confidence interval is retrieved, and the first confidence level is compared with the upper and lower limit values of the first confidence interval to determine whether the first confidence level is within the first confidence interval. If so, it can be considered that the association relationship between the corresponding two APIs is established; otherwise, it can be considered that the association relationship between the corresponding two APIs is not established, and no further analysis of association factors needs to be performed on the two APIs without an association relationship. In some other embodiments, for the preset credibility indicating that the association relationship between two APIs is established, it can also be determined as the first confidence threshold (such as 85%, etc., and the present application does not limit its value). If the detected first confidence level (such as 90%, etc.) reaches the first confidence threshold, it can be considered that there is an association relationship between these two APIs. The present application does not limit the implementation method for detecting whether the association relationship between two APIs is established.

[0108] According to the association analysis implementation method described above in the present application, for each API pre-developed on the low-code platform, usually at least one other API associated with it can be determined, denoted as the associated API list. It should be noted that there may be an association relationship between multiple APIs bound to the same interaction form. For example, the delete API, modify API, detail API, etc. bound to the list API may have an association relationship, and there may also be APIs without an association relationship among these bound APIs, and the association analysis can be determined according to the method described above. Similarly, for the same type of APIs bound to different interaction forms under the same application, and for the same type of APIs bound to the same or different interaction forms under different applications, due to possible differences in API parameters and other information, there may or may not be an association relationship between the same type of APIs, which depends on the situation.

[0109] Step S46, using the API parameter call data between any two APIs with an association relationship, statistically calculate the second co-occurrence probability of each API parameter in different API calls;

[0110] According to the method described above in the present application, after determining that there is an association relationship between two APIs, it is possible to further determine what the association factors are that cause these two APIs to have an association relationship. For example, due to what API parameters these two APIs are bound to the same interaction form, bound to different interaction forms of the same application, etc. In this regard, the present application proposes to record the call data of APIs and their API parameters for each interaction form accessed during the operation of the low-code published application. During the above data sampling stage, the API parameter call data can be collected, and using the association analysis algorithm, analyze the parameter call data of the APIs with an association relationship to determine the corresponding association factors.

[0111] In some embodiments, based on co-occurrence probability statistics and confidence analysis, the parameter correspondence between APIs with an association relationship can be determined, that is, the association factors of the associated APIs are determined. Therefore, the present application can perform co-occurrence probability statistics on a large number of API parameter call data of associated APIs obtained, and determine the second co-occurrence probability of each API parameter in different API calls. Generally, the higher the second co-occurrence probability of a certain API parameter in different API calls, the higher the probability that the API parameter is an association factor that makes the corresponding two APIs have an association relationship. The statistical implementation method of the second co-occurrence probability in the present application will not be elaborated in detail, and it can be determined in combination with the operation principle of co-occurrence probability statistics.

[0112] It should be noted that for some of the already determined APIs with an association relationship, there may be no API parameter correspondence. This often means that the association relationship between these two APIs is established through the application scenario. Therefore, in the analysis process of the association relationship between each pair of APIs above, it can be determined not only based on API parameters, but also in combination with the API application scenario. For example, different APIs applicable to the same application scenario may have an association relationship, which can be determined according to at least one pre-configured association relationship analysis condition.

[0113] Step S47: Obtain the second confidence level that each API parameter makes the corresponding two APIs have an association relationship based on the second co-occurrence probability;

[0114] Step S48: If the second confidence level is within the second confidence interval, determine the corresponding API parameter as the association factor that makes the corresponding two APIs have an association relationship;

[0115] Combined with the relevant description of the first conversion rule of the first co-occurrence probability and the first confidence level in the above embodiments, the present application can also pre-determine the second conversion rule between the second co-occurrence probability and the second confidence level. The second conversion rule may be the same as or different from the first conversion rule, which can be determined according to the actual analysis results. The content of each conversion rule in the present application will not be elaborated in detail. According to the second conversion rule, the present application uses the obtained second co-occurrence probability to convert and obtain the second confidence level that the API parameter is the association factor of the corresponding two associated APIs, that is, the second confidence level that the API parameter affects the association relationship between these two APIs.

[0116] It can be understood that the influence direction of the same API parameter on the association relationship of different groups of APIs may be different. It may increase the probability that the association relationship between the two APIs in this group holds; it may also increase the probability that the association relationship between the two APIs in this group does not hold. Therefore, the second confidence level of the same API parameter on the association relationship of different groups of APIs may be different.

[0117] Since the second confidence level represents the credibility of the corresponding API parameter for the establishment of the association relationship between two APIs, and the higher the second confidence level, the greater the positive influence of the API parameter in determining the association relationship between the two APIs. Therefore, in the second confidence interval where the preset API parameter becomes an associated factor for the association relationship between two APIs, that is, within what credible range the confidence level of the API parameter reaches, if it is considered that the API parameter is an associated factor affecting the association relationship between the two APIs, the obtained second confidence level can be compared with the second confidence interval. If the second confidence level is within the second confidence interval, it is determined that the corresponding API parameter is the associated factor for the establishment of the association relationship between the corresponding two APIs. As Figure 3 shown, the associated factors between API1 and API2 include parameter 1, and the associated factors between API2 and API3 include parameter 4; conversely, the corresponding API parameter can be considered as a differentiating factor between the corresponding two APIs.

[0118] Among them, in the analysis process of the above-mentioned associated factors, information such as the second co-occurrence probability of the API parameter in the two associated APIs and the degree of association between the API parameter and the API application scenario can be combined to determine the second confidence level of the API parameter for the association of the corresponding two APIs. This application does not limit the acquisition methods of the above-mentioned confidence levels.

[0119] It should be noted that the above-mentioned association relationship can include a direct association relationship, such as Figure 3 the association relationship between API1 and API2, the association relationship between API2 and API3, and the association relationship between API1 and API4 shown; it can also include an indirect association relationship, such as the association relationship between AP1 and API3. In this case, the associated factors between the two can include parameter 1 of AP1 and parameter 4 of API2, but it is not limited to Figure 3 the shown association relationship.

[0120] Step S49, generate API relationship topology data according to the association relationship and associated factors between different APIs.

[0121] As Figure 5 shown, for the generated API relationship topology data, it can be sent to the database for storage for subsequent retrieval by the client when querying the target API. This application does not limit the storage implementation method of the API relationship topology data and can be determined according to the situation.

[0122] In summary, in the embodiments of the present application, by obtaining the configuration data of each interaction form under a large number of published applications and performing correlation analysis, the associated API list of each API is determined, that is, it is determined whether the association relationship between every two APIs is established; then, by obtaining the API parameter call data generated during the operation of the published application when operating on the interaction forms therein, after correlation analysis, the association factors between two APIs with an association relationship are further determined. After that, the association relationship and association factors between any two pre-developed APIs on the low-code platform can be combined to generate an API relationship topology to supplement the API information. Through the API relationship topology data, a large number of pre-developed APIs on the low-code platform can be recorded more clearly and orderly, that is, each API can be depicted more accurately and comprehensively, which helps to quickly and accurately query and locate the required target API from a large number of APIs.

[0123] Among them, for the above-mentioned correlation analysis algorithm, the present application proposes a co-occurrence probability statistics and confidence analysis method to determine whether the association relationship between different APIs is established and what the association factors are between two APIs with an established association relationship, so as to quickly and accurately generate the relationship topology structure between a large number of pre-developed APIs on the low-code platform. Of course, the present application can also adopt other correlation analysis algorithms to implement the analysis of API association relationships and association factors, which will not be elaborated herein.

[0124] In some other embodiments proposed by the present application, the present application can also pre-construct an API correlation analysis model, such as based on a conditional probability algorithm (such as Bayesian conditional probability, etc.), analyze the collected sample data, and construct an API correlation analysis model to determine whether the association relationship between any two APIs is established and the association factors between the APIs with an established association relationship. Therefore, after the data sampling is completed according to the above method, the pre-constructed API correlation analysis model can be retrieved, and the relevant data of the interaction form obtained (such as the configuration data of each interaction form, API parameter call data, etc.) is input into the API correlation analysis model to obtain the list of APIs associated with the API itself bound by the interaction form of the published application, and the association factors between the API and any API in the list of APIs associated with itself. The implementation process will not be elaborated herein.

[0125] Refer to Figure 6 , which is a schematic flowchart of another optional example of the interaction information processing method proposed by the present application. This embodiment can be another optional refined implementation method of the interaction information processing method described above. Combining the API relationship topology data generation method described in the above embodiments, the pre-generated API relationship topology data is used to quickly and accurately query the required target API from a large number of APIs to meet the subsequent processing requirements of the target API. Such asFigure 6 As shown in Figure 6 , the interactive information processing method proposed in this embodiment may include but is not limited to the following steps:

[0126] Step S61, obtain an API processing request for a target API corresponding to a to-be-processed interactive form for a target application;

[0127] Step S62, obtain the information to be queried carried by the API processing request;

[0128] Combined with the relevant description of the API processing request in the above embodiment, the computer device obtains the request content included therein by parsing the API processing request, which is recorded as the information to be queried. Among them, as analyzed above, the information to be queried may be determined based on the target API parameters of the target API, and the information to be queried may also be determined in combination with the form data of the to-be-processed interactive form as needed. In practical applications, the information to be queried may include but is not limited to the keywords of the target API, and may also include the description information for describing the target API, etc., which can be determined according to the situation and will not be elaborated in this application.

[0129] Step S63, query the generated API relationship topology data to obtain multiple candidate APIs that match the information to be queried, as well as the associated APIs and the corresponding candidate associated factors that have an association relationship with the candidate APIs;

[0130] Combined with the relevant description of the API relationship topology data above, after this application determines the information to be queried for the target API, that is, the information for determining which one or more APIs are the target APIs, it can use the information to be queried to query the API relationship topology data. For example, the information to be queried is matched with the API information of each API included in the API relationship topology data (such as API parameters, etc. This API information may be the basic API information, which can be queried in the API information model data through its own API identifier and does not require being recorded in the API relationship topology data. That is to say, the API relationship topology data can record the API identifier to obtain the API information corresponding to the corresponding API, and the implementation process will not be elaborated in this application), and multiple candidate APIs that may be the target APIs are roughly selected from a large number of APIs. Among them, the candidate API refers to an API whose matching degree between the API information and the information to be queried reaches a matching threshold (the value of which is not limited in this application and can be determined according to the situation), and it can be implemented through but is not limited to the similarity algorithm, and the implementation process will not be elaborated in this application.

[0131] After that, for each candidate API retrieved, the associated API list of the candidate API, the API parameters of each associated API, and the association factors between the candidate API and each associated API can be determined through the API relationship topology recorded in the API relationship topology data. In this embodiment, the association factors between the candidate API retrieved here and its associated APIs are denoted as candidate association factors.

[0132] Among them, for each API in the API relationship topology data, a corresponding API identifier can be configured to distinguish different APIs; for APIs with different identities, corresponding identity identifiers representing the identities can be configured. For example, for each associated API in the associated API list of APIx, an association identifier indicating the association with APIx can be configured, denoted as an associated API identifier. It can be understood that for the same API, it can have its own API identifier, and in the case where it is associated with multiple other APIs, corresponding associated API identifiers corresponding to each association with other APIs can be configured for it, such that the API has corresponding multiple associated API identifiers, but it is not limited to this recording method.

[0133] Based on this, during the process of querying the associated API list of the candidate API above, the associated API list can be searched according to the API identifier of the candidate API. For example, the associated APIs with the associated API identifiers corresponding to the candidate API can be searched. At this time, each associated API included in the retrieved associated API list can be represented by its respective corresponding API identifier, but it is not limited to this way of representing the query result, and the content of the above-mentioned API identifiers and associated API identifiers in this application is not limited and can be numbers, letters, characters, etc.

[0134] Step S64, screen out the target API from multiple candidate APIs according to the API parameters of the associated API and the corresponding candidate association factors;

[0135] For each candidate API retrieved, this application can further analyze its associated APIs, the API parameters and association factors they contain to determine whether the candidate API is the required target API. Compared with the query method of directly matching through the information to be queried to determine the target API, the query accuracy of the target API is greatly improved.

[0136] In some embodiments, the computer device can match and analyze the information such as the associated APIs of each candidate API, the API parameters and association factors they contain with the information to be queried again, and can also combine the form data of the form to be processed, or even the comparison between the information of multiple candidate APIs themselves to comprehensively determine the target API.

[0137] In some other embodiments, the present application can also output multiple candidate APIs retrieved in a relational topology graph. A front-end developer can select a certain candidate API from it, and the associated API list of the selected candidate API can be presented on the current information output interface. Even the associated factors corresponding to each associated API can be presented, or a certain associated API can be further selected from the associated API list to view the associated factors between the candidate API and the associated API. The present application does not limit the output method of the above query results and can be determined according to the situation. For the output method described in these other embodiments, it can assist the front-end developer to quickly and accurately determine the required target API from multiple candidate APIs. The selection implementation process is not described in detail in the present application.

[0138] It can be seen that through the API relational topology data, the present application can quickly and accurately query the target API of the interaction form to be processed, as well as the associated API list of the target API, that is, each associated API having an associated relationship with the target API, the API information, associated factors, etc. of each associated API, for developers to view the relevant information of the target API, and can optimize the application / interaction form to be processed accordingly.

[0139] Step S65: Bind the retrieved target API identifier to the interaction form to be processed;

[0140] Step S66: Update the API relational topology data according to the binding relationship between the interaction form to be processed and the target API.

[0141] In the embodiments of the present application, after quickly and accurately querying the target API corresponding to the interaction form to be processed by using the pre-generated API relational topology data, a preset operation can be executed according to the current business requirements based on the target API, such as Figure 5 As shown, in the application development scenario, for a newly designed interaction form, the target APIs to be bound can be queried according to the method described above, that is, in the low-code development process, the target API can be quickly and accurately queried / located through the API relational topology data. Then, the target API identifier of the target API can be bound to the interaction form to complete the application development design, improving the application development efficiency and reliability.

[0142] After the binding relationship between the newly generated interaction form and the target API, it may affect the associated relationships between the APIs in the existing API relational topology data; the use of the interaction form for the developed application may also affect the associated factors between the associated APIs. Therefore, the present application can regenerate the API relational topology data according to the newly constructed binding relationship, the API information of the target API, the newly designed interaction form, and even the API parameter call data generated by the use of the interaction form, according to the method described above.

[0143] To reduce the workload, this application can also analyze whether the influence of these data on the association relationships and associated factors in the currently existing API relationship topology data reaches a threshold. If it reaches the threshold, it indicates that these data will cause changes in the association relationships and associated factors between the existing APIs. The association relationships and associated factors can be updated in combination with these data, such as adding new association relationships and / or associated factors, modifying the existing association relationships and / or associated factors, etc. This application does not limit the implementation method for this update and can be determined according to the situation. If it does not reach the threshold, it indicates that these data will not cause changes in the association relationships and associated factors between the existing APIs, and there is no need to update the API relationship topology data.

[0144] It should be noted that regarding the preset operations performed after the query result of the target API obtained by this application, it includes but is not limited to the binding operation described in this embodiment. For example, in the API optimization scenario, the query result of the target API can also be output for the back-end developer to optimize the API information accordingly, and then update the optimized API information to the API relationship topology data, or re-determine the API relationship topology according to the method described above. The implementation process is not described in detail in this application.

[0145] Refer to Figure 7 , which is a schematic structural diagram of an optional example of the interaction information processing device proposed by this application. The device may include:

[0146] The API processing request acquisition module 71 is used to acquire an API processing request for a target application programming interface (API) corresponding to a to-be-processed interaction form for a target application.

[0147] The target API query module 72 is used to query the generated API relationship topology data in response to the API processing request. Among them, the API relationship topology data can characterize the association relationships and associated factors between the APIs bound to different published interaction forms.

[0148] The processing module 73 is used to perform a preset operation according to the query result of the target API queried.

[0149] In some embodiments, in order to generate the above-mentioned API relationship topology data, as Figure 8 shown, the interaction information processing device proposed by this application may further include:

[0150] The data acquisition module 74 is used to acquire the relevant data of the interaction forms of the published applications.

[0151] An association analysis module 75 is configured to perform an association analysis on the relevant data of the interaction form to determine the association relationships and association factors between different APIs bound to each interaction form;

[0152] A relationship topology generation module 76 is configured to generate API relationship topology data based on the association relationships and association factors between the different APIs.

[0153] In some embodiments, the above data acquisition module 74 may include:

[0154] A configuration data acquisition unit is configured to acquire the configuration data of the interaction forms of the published application;

[0155] A parameter call data acquisition unit is configured to acquire the parameter call data generated by accessing the interaction forms under the published application;

[0156] In this regard, the above association analysis module 75 may include:

[0157] A first association analysis unit is configured to perform an association analysis on the configuration data of the interaction form to determine the association relationships between different APIs bound to each interaction form;

[0158] A second association analysis unit is configured to perform an association analysis on the parameter call data to determine the association factors between different APIs having the association relationships.

[0159] Based on the above analysis, in still some other embodiments, the above data acquisition module 74 may include:

[0160] A first acquisition unit is configured to acquire the binding relationships between different interaction forms and different APIs of the published application, and the API parameters corresponding to the different APIs; the API parameters represent the output information in the interaction form having a binding relationship with the corresponding API;

[0161] A second acquisition unit is configured to acquire the API parameter call data of any interaction form during the process of responding to an access request for the interaction form of the published application.

[0162] Based on this, the above first association analysis unit may include:

[0163] A first co-occurrence probability statistics unit is configured to statistically calculate the first co-occurrence probability between any two APIs according to the API parameters of each API, the interaction form bound thereto, and the published application category to which the interaction form belongs;

[0164] A first confidence level acquisition unit is configured to acquire the first confidence level that there is an association relationship between the corresponding two APIs according to the first co-occurrence probability;

[0165] An association relationship determination unit, configured to determine that there is an association relationship between two corresponding APIs when the first confidence level is within the first confidence interval.

[0166] Optionally, the second association analysis unit may include:

[0167] A second co-occurrence probability statistics unit, configured to use the API parameter call data between any two APIs having the association relationship to statistically calculate the second co-occurrence probability of each API parameter in different API calls;

[0168] A second confidence level obtaining unit, configured to obtain a second confidence level that the corresponding two APIs have an association relationship based on the second co-occurrence probability;

[0169] An association factor determination unit, configured to determine the corresponding API parameter as an association factor that enables the corresponding two APIs to have an association relationship when the second confidence level is within the second confidence interval.

[0170] In some other embodiments proposed in the present application, the above-mentioned association analysis module 75 may further include:

[0171] A model retrieval unit, configured to retrieve an API association analysis model; the API association analysis model is constructed based on a conditional probability algorithm;

[0172] A model analysis unit, configured to input the relevant data of the interaction form into the API association analysis model, and obtain a list of APIs associated with the APIs bound to the interaction form of the published application, and an association factor between the API and any API in the list of APIs associated with itself.

[0173] Based on the interaction information processing device described in the above embodiments, as Figure 9 shown, the target API query module 72 in the above embodiments may include:

[0174] A to-be-query information acquisition unit 721, configured to acquire to-be-query information carried in the API processing request; the to-be-query information is determined based on the target API parameter of the target API;

[0175] A candidate information obtaining unit 722, configured to query the generated API relationship topology data, obtain multiple candidate APIs that match the to-be-query information, as well as associated APIs associated with the candidate APIs and corresponding candidate association factors;

[0176] A target API screening unit 723, configured to screen out the target API from the multiple candidate APIs according to the API parameters of the associated API and the corresponding candidate association factors;

[0177] In this regard, in some embodiments, as Figure 9 shown, the above processing module 73 may include:

[0178] A binding unit 731, configured to bind the identified target API obtained by query to the to-be-processed interaction form;

[0179] An update unit 732, configured to update the API relationship topology data according to the binding relationship between the to-be-processed interaction form and the target API.

[0180] It should be noted that, for various modules, units, etc. in the above device embodiments, they can all be stored as program modules in the memory, and the processor executes the above program modules stored in the memory to implement corresponding functions. For the functions implemented by each program module and its combination, and the achieved technical effects, reference can be made to the description of the corresponding part of the above method embodiments, and details are not described in this embodiment.

[0181] The present application also provides a computer-readable storage medium, on which a computer program can be stored. The computer program can be called and loaded by a processor to implement each step of the interaction information processing method described in the above embodiments. The implementation process can refer to the description of the corresponding part of the above embodiments, and details are not described in this embodiment.

[0182] Referring to Figure 10 , it is a schematic hardware structure diagram of an optional example of a computer device applicable to the interaction information processing method proposed in the present application. As analyzed above, the computer device can be a terminal device or a service device. Taking the service device as an example for illustration, as Figure 10 shown, its hardware structure composition may include but is not limited to: at least one communication interface 101, at least one memory 102, and at least one processor 103, where:

[0183] The communication interface 101 can be the data interface of the communication module, supporting data communication between the computer device and other external devices and internal components. This application does not limit the type and quantity of the communication interface 101, which can be determined according to the situation. Among them, the communication module can include a communication module capable of realizing data interaction using a wireless communication network, such as a WIFI module, a 5G / 6G (fifth-generation mobile communication network / sixth-generation mobile communication network) module, a GPRS module, a near-field communication module, a GMS module, etc. The communication interface types and supported communication protocols of different communication modules may be different, and can be determined according to the communication requirements of the communication module. This application does not elaborate on them one by one.

[0184] Among them, in order to realize the communication of the internal components of the computer device, the above communication interface 101 can also include a USB interface, a serial / parallel port, a multimedia data interface, etc., which can be determined according to the product type and configuration requirements of the computer device. This application does not list them one by one.

[0185] The memory 102 can be used to store the program for implementing the interactive information processing method described in the above method embodiments; the processor 1103 can load and execute the program stored in the memory 102 to implement each step of the interactive information processing method described in the above corresponding method embodiments. The specific implementation process can refer to the description of the corresponding part of the above embodiments, and this embodiment will not be elaborated here.

[0186] In practical applications, the communication interface 101, the memory 102, and the processor 103 can be connected to a communication bus, and data interaction between them and other structural components of the computer device can be realized through this communication bus, which can be specifically determined according to actual needs. This application does not elaborate on it.

[0187] In the embodiments of this application, the memory 102 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device or other volatile solid-state storage devices. The processor 103 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, etc. This application does not limit the structures and models of the above memory 102 and processor 103, and can be flexibly adjusted according to actual needs.

[0188] It should be understood that Figure 10 the structure of the shown computer device does not constitute a limitation on the computer device in the embodiments of this application. In practical applications, the computer device can include moreFigure 10 more components as shown, or combine certain components. For example, when the computer device is a terminal device, the computer device may further include at least one input component such as a touch sensing unit for sensing touch events on the inductive touch display panel, a keyboard, a mouse, a camera, a pickup, etc.; at least one output component such as a display, a speaker, a vibration mechanism, a light, etc.; an antenna; a sensor module; a power module, etc., and the hardware structure can be determined according to the type of the terminal device and its functional requirements; when the computer device is a service device, the computer device may further include a monitoring device, a database, etc., which are not listed one by one in this application.

[0189] Finally, it should be noted that in the above embodiments, unless the context clearly indicates an exception, words such as "a", "an", "one" and / or "the" are not specifically singular and may also include plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. A method or device may also include other steps or elements. An element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, product or device including the element.

[0190] Among them, in the description of the embodiments of the present application, unless otherwise specified, " / " means "or". For example, A / B may mean A or B; the "and / or" herein is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "a plurality of" means two or more than two.

[0191] Terms involved in the present application such as "first", "second", etc. are only for descriptive purposes, used to distinguish one operation, unit or module from another operation, unit or module, and do not necessarily require or imply any such actual relationship or order between these units, operations or modules. And it cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second" may explicitly or implicitly include one or more of such features.

[0192] In addition, the various embodiments in this specification are described in a progressive or parallel manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other. For the devices and computer devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0193] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An interactive information processing method, the method comprising: Obtaining an API processing request for a target application programming interface (API) corresponding to a to-be-processed interactive form for a target application; Responding to the API processing request and querying generated API relationship topology data; wherein the API relationship topology data can represent the association relationship and association factors between APIs bound to different published interactive forms; Performing a preset operation according to the query result of the target API; Wherein, the method for generating the API relationship topology data includes: Obtaining configuration data of interactive forms of a published application and parameter call data generated by accessing the interactive forms; Performing a correlation analysis on the configuration data of the interactive forms and the parameter call data to determine the association relationship and association factors between different APIs bound to each interactive form; Generating API relationship topology data according to the association relationship and association factors between the different APIs.

2. The method according to claim 1, wherein the performing a correlation analysis on the configuration data of the interactive forms and the parameter call data to determine the association relationship and association factors between different APIs bound to each interactive form includes: Performing a correlation analysis on the configuration data of the interactive forms to determine the association relationship between different APIs bound to each interactive form; Performing a correlation analysis on the parameter call data to determine the association factors between different APIs having the association relationship.

3. The method according to claim 1, wherein the obtaining configuration data of interactive forms of a published application and parameter call data generated by accessing the interactive forms includes: Obtaining the binding relationship between different interactive forms and different APIs of a published application and the API parameters corresponding to the different APIs; The API parameters represent output information in the interactive form having a binding relationship with the corresponding API; Obtaining parameter call data of an API of an interactive form during the process of responding to an access request for any interactive form of the published application.

4. The method according to claim 3, wherein the performing a correlation analysis on the configuration data of the interactive forms to determine the association relationship between different APIs bound to each interactive form includes: Statistically calculating a first co-occurrence probability between any two APIs according to the API parameters of each API, the interactive form bound thereto, and the category of the published application to which the interactive form belongs; Obtaining a first confidence level of an association relationship between the corresponding two APIs according to the first co-occurrence probability; If the first confidence level is within a first confidence interval, determining that there is an association relationship between the corresponding two APIs.

5. The method according to claim 2, wherein the performing a correlation analysis on the parameter call data to determine the association factors between different APIs having the association relationship includes: Statistically calculating a second co-occurrence probability of each API parameter in different API calls by using the API parameter call data between any two APIs having the association relationship; Obtain a second confidence level for each of the API parameters to have an association relationship between the corresponding two APIs according to the second co-occurrence probability; If the second confidence level is within the second confidence interval, determine the corresponding API parameter as an association factor for having an association relationship between the corresponding two APIs.

6. The method according to claim 1, wherein the performing correlation analysis on the configuration data of the interaction form and the parameter call data to determine the association relationship and association factors between different APIs bound to each interaction form includes: Retrieve an API correlation analysis model; The API correlation analysis model is constructed based on a conditional probability algorithm; Input the configuration data of the interaction form and the parameter call data into the API correlation analysis model to obtain a list of APIs associated with the APIs bound to the interaction forms of the published application, and the association factors between the API and any one of the APIs in the list of APIs associated with itself.

7. The method according to any one of claims 1-6, wherein the responding to the API processing request and querying the generated API relationship topology data includes: Obtain the information to be queried carried by the API processing request; The information to be queried is determined based on the target API parameter of the target application programming interface API; Query the generated API relationship topology data to obtain multiple candidate APIs that match the information to be queried, and the associated APIs having an association relationship with the candidate APIs and the corresponding candidate association factors; Screen out the target application programming interface API from the multiple candidate APIs according to the API parameter of the associated API and the corresponding candidate association factor; The performing a preset operation according to the query result of the queried target application programming interface API includes: Bind the identifier of the queried target application programming interface API to the to-be-processed interaction form; Update the API relationship topology data according to the binding relationship between the to-be-processed interaction form and the target application programming interface API.

8. An interaction information processing device, the device includes: A data acquisition module, configured to acquire the configuration data of the interaction forms of the published application, and the parameter call data generated by accessing the interaction forms; An association analysis module, configured to perform correlation analysis on the configuration data of the interaction form and the parameter call data to determine the association relationship and association factors between different APIs bound to each interaction form; A relationship topology generation module, configured to generate API relationship topology data according to the association relationship and association factors between the different APIs; An API processing request acquisition module, configured to acquire an API processing request for a target application programming interface API corresponding to a to-be-processed interaction form of a target application; A target API query module, configured to respond to the API processing request and query the generated API relationship topology data; wherein the API relationship topology data can represent the association relationship and association factors between the APIs bound to different published interaction forms. A processing module, configured to perform a preset operation according to a query result of the queried target application programming interface (API).

9. A computer device, the computer device comprising: At least one communication interface, at least one memory, and at least one processor, wherein: The memory is configured to store a program of the interactive information processing method according to any one of claims 1-7; The processor is configured to load and execute the program in the memory to implement the interactive information processing method according to any one of claims 1-7.

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