CN114185915A - Service processing method and device - Google Patents
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Abstract
The application provides a service processing method and a device, wherein the service processing method comprises the following steps: receiving a service flow request, wherein the service flow request carries a target service identifier of a target object; determining a target service circulation rule corresponding to the target node in a rule base based on the target service identification, wherein the rule base is generated based on a discrete parallel model; determining target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identification, wherein the feature domain is generated based on a discrete parallel model; and analyzing the target attribute information based on the target service flow rule to obtain a flow result.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a service processing method. The application also relates to a business processing device, a computing device and a computer readable storage medium.
Background
With the continuous development of computer technology, the requirements of users for information auditing are also increasing, for example, for pictures uploaded to a public platform, besides whether the pictures meet the requirements of regulations or not, picture attributes such as picture definition of the pictures can also be audited; in order to meet different auditing requirements of users for information, a corresponding auditing rule needs to be formulated for each auditing requirement for information auditing.
However, the setting mode of the audit rule is various, the audit scene is complex, when the audit rule is used for auditing the attribute information of the service, each audit rule needs to be analyzed one by one, so that the information audit is realized.
Therefore, how to implement multi-dimensional auditing of service attribute information is a technical problem to be solved urgently by those skilled in the art.
Disclosure of Invention
In view of this, an embodiment of the present application provides a service processing method. The application also relates to a business processing device, a computing device and a computer readable storage medium, which are used for solving the problems of low analysis efficiency and single audit rule in the prior art.
According to a first aspect of the embodiments of the present application, there is provided a service processing method applied to a target node of a discrete parallel model, including:
receiving a service flow request, wherein the service flow request carries a target service identifier of a target object;
determining a target service circulation rule corresponding to the target node in a rule base based on the target service identification, wherein the rule base is generated based on a discrete parallel model;
determining target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identification, wherein the feature domain is generated based on a discrete parallel model;
and analyzing the target attribute information based on the target service flow rule to obtain a flow result.
According to a second aspect of the embodiments of the present application, there is provided a service processing apparatus applied to a target node of a discrete parallel model, including:
the system comprises a receiving module, a service flow processing module and a service flow processing module, wherein the receiving module is configured to receive a service flow request, and the service flow request carries a target service identifier of a target object;
a first determining module configured to determine a target service flow rule corresponding to the target node based on the target service identifier in a rule base, wherein the rule base is generated based on a discrete parallel model;
the second determining module is configured to determine target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identifier, wherein the feature domain is generated based on a discrete parallel model;
and the analysis module is configured to analyze the target attribute information based on the target service flow rule to obtain a flow result.
According to a third aspect of embodiments of the present application, there is provided a computing device comprising a memory, a processor and computer instructions stored on the memory and executable on the processor, the processor implementing the steps of the business process method when executing the computer instructions.
According to a fourth aspect of embodiments of the present application, there is provided a computer-readable storage medium storing computer instructions which, when executed by a processor, implement the steps of the business processing method.
The service processing method provided by the application receives a service flow request, wherein the service flow request carries a target service identifier of a target object; determining a target service circulation rule corresponding to the target node in a rule base based on the target service identification, wherein the rule base is generated based on a discrete parallel model; determining target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identification, wherein the feature domain is generated based on a discrete parallel model; and analyzing the target attribute information based on the target service flow rule to obtain a flow result.
In the service processing method provided by the embodiment of the application, the target service flow rule corresponding to the target node is determined based on the target service identifier, so that the specific change of each rule can be conveniently and visually known; target attribute information of the target object is analyzed based on the target service flow rule to obtain a flow result, so that multi-aspect analysis of the target attribute information is realized, and the comprehensiveness of auditing is improved.
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Fig. 1 is a flowchart of a service processing method according to an embodiment of the present application;
fig. 2 is a processing flow chart of a service processing method applied to review service according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a service processing apparatus according to an embodiment of the present application;
fig. 4 is a block diagram of a computing device according to an embodiment of the present application.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of implementation in many different ways than those herein set forth and of similar import by those skilled in the art without departing from the spirit of this application and is therefore not limited to the specific implementations disclosed below.
The terminology used in the one or more embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the present application. As used in one or more embodiments of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present application is intended to encompass any and all possible combinations of one or more of the associated listed items.
It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments of the present application to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first aspect may be termed a second aspect, and, similarly, a second aspect may be termed a first aspect, without departing from the scope of one or more embodiments of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
First, the noun terms to which one or more embodiments of the present application relate are explained.
Discrete parallel model: a system model suitable for describing concurrency phenomena can be represented by a mesh graph, such as a petri net, wherein state elements and change elements in the net are represented by nodes and transitions respectively, each node represents a resource, the transitions represent changes causing resource flow, the flow relation describes the flow direction of the resource, the transitions can only have direct flow relation with the nodes, and only one isolated node or transition of the petri net is supported. The individual attributes of the resources established in the relationships of nodes, transitions and streams are called feature tokens.
Colored petri nets: on the basis of the petri net, resource categories are distinguished, the same type of resource individuals are dyed with the same color, and different types of resource individuals are dyed with different colors.
At present, more and more information and content products are encouraged to be actively shared by users, and in order to improve the sharing and using experience of the users, a platform can make an audit rule, filter bad content and display high-quality content. According to the content display form, the content is divided into characters, pictures, videos and audios, the auditing rules of each type of content are different, and even if the content belongs to the same type of videos, the auditing requirements of short videos and long videos are different. The auditing rules of part of services comprise timing tasks, the triggering of part of rules is triggered by a third party service, and the auditing scenes such as the type are complex and various, so that a set of general flow rule framework is difficult to abstract, and the conventional scheme is to realize each auditing rule in a customized manner at present.
However, customized audit rules cannot be dynamically expanded, the multiplexing capability is low, and the development cost is high; secondly, if the specific change of a rule is known from the codes, the difficulty is high, and especially a complex rule is dispersed in a plurality of project codes, and a complete influence range of the rule is difficult to summarize through a plurality of iterations. Furthermore, the audit rule is limited to the attribute of one content individual, and cannot be applied to the audit rule containing both resource constraint and time constraint.
The business processing method can solve the phenomenon that the current auditing rule is limited to 'content attribute logic comparison', and can be expanded to a plurality of dimensions of resource constraint and time constraint of the context of the whole auditing scene. And the feature token participates in the visual arrangement of the auditing rules, so that the specific change of each rule can be conveniently and visually known.
In the present application, a service processing method is provided, and the present application relates to a service processing apparatus, a computing device, and a computer-readable storage medium, which are described in detail in the following embodiments one by one.
Fig. 1 shows a flowchart of a service processing method provided in an embodiment of the present application, which specifically includes the following steps:
step 102: receiving a service flow request, wherein the service flow request carries a target service identifier of a target object.
The service flow request refers to a request for transferring a target object between nodes of a discrete parallel model, wherein the discrete parallel model refers to a model formed by the nodes, transitions and connection arcs between the nodes and the transitions, the target object can be transferred between the nodes of the discrete parallel model, each node or transition has a corresponding service flow rule, and the transfer direction of the target object between the nodes and the library of the discrete parallel model can be determined based on the service flow rules; the target node of the discrete parallel model refers to any one of a plurality of nodes of the discrete parallel model which needs to be subjected to flow processing; the target object refers to an object in a target service, for example, a picture to be audited in a picture auditing service, a video to be audited in a video auditing service, and the like; the target service identifier refers to a field for uniquely identifying the target service, for example, an identifier "picture audit" of a picture audit service; the target service that the target object needs to execute may be determined based on the target service identifier of the target object, for example, if the service identifier of the picture a is "picture size audit", it is determined that the picture a needs to perform picture size audit, and if the service identifier of the picture a is "picture source audit", it is determined that the picture a needs to perform picture source audit.
In practical application, a service flow request may be generated by triggering execution of a target service in a discrete parallel model, specifically, a service flow request is generated based on a target service identifier of the target service, for example, a service flow request is generated by triggering execution of a video size auditing service in the discrete parallel model, that is, an audit of a video to be audited in a subsequent video size auditing service may be realized by flowing between nodes of the discrete parallel model, each video to be audited corresponds to a video size auditing identifier, and a video size required for the video to be audited may be determined based on the video size auditing identifier.
In a specific embodiment of the present application, taking a picture sharpness audit service as an example, a service flow request is received, and a target service identifier "picture sharpness audit" in the service flow request is determined; determining that the target service is a picture definition auditing service according to the target service identifier 'picture definition auditing'; the pictures to be audited in the picture definition audit service are all corresponding to target service identification 'picture definition audit'.
The target service identification corresponding to the target object which is circulated between the nodes of the discrete parallel model can be determined through the received service circulation request, the target service can be determined based on the target service identification, and the circulation of the target object between the nodes of the discrete parallel model can be realized conveniently based on the subsequent service processing rule corresponding to the target service.
In practical applications, in order to implement the flow of a target object between nodes of a discrete parallel model, before receiving a service flow request, a discrete parallel model needs to be created based on service information related to a target service, and specifically before receiving the service flow request, the method further includes:
receiving target attribute information of a target service, and generating a feature domain according to the target attribute information;
and creating a feature token based on the feature domain, and generating a rule base according to the feature token.
Wherein the target attribute information refers to information related to the target service, such as user ID, user information, title information, profile, etc.; the target attribute information may include service content information, service rule information, and service flow information related to the target service, where the service content information refers to attribute information of the target object, for example, the target service is a picture definition audit, the content information may be attribute information of a picture to be audited, including picture size information, and the like, the service rule information refers to rule information when the target object is determined to be streamed in the discrete parallel model, for example, the rule information refers to attribute information of a node where the picture size information exceeds 100k to be audited or a transition in the streaming process of the target object, for example, the flow information refers to attribute information of a transition from a first audit node to a second audit node of the picture to be audited.
The feature domain refers to a set of target attribute information, and under the condition that the feature domain of the current discrete parallel model does not contain attribute information, the feature domain is formed by the target attribute information, if the attribute information is contained in the feature domain of the current discrete parallel model, the attribute information which is overlapped with the attribute information of the feature domain in the target attribute information is ignored, and attribute information which does not overlap with the attribute of the feature domain is added to the feature domain, the attribute information in the feature domain shares a set of attribute field names, for example, a system allocates a service number to a target service, when a new service is accessed in the discrete parallel model, the service meaning, the optional value range, the associated information value mode, the set value mode and the like of each attribute field need to be bound, so that the aim of accessing different attributes of each service in the same mode is fulfilled, and meanwhile, the service attribute also needs to be registered.
The feature token is an attribute information judgment field created by taking a feature domain as a data source, and includes variables, calculation types and values, where the variables and the values need to be compatible or can be automatically converted, and the variables and the values may be feature access paths, and the variables may be attribute values of a target object, for example, the picture size of a picture to be audited is 300 k.
The calculation type refers to a type of calculating an attribute value of the target object, and the calculation type includes an assigned value class (e.g., equal to), a singleton operation class (e.g., negation, existence, absence), a comparison class (e.g., equal to, not equal to, greater than, within an upper boundary, not within a lower boundary), a matching class (e.g., a value in a list, a list existence value, a regular matching value, etc.), an aggregation class (e.g., a maximum value, a minimum value, a total number, etc.), and the value may be a threshold value or a threshold field set based on the target business rule, for example, a picture size 100k, a state to be audited, etc.
And creating a characteristic token based on the rule information in the target attribute information, creating a business flow rule of the target object according to the characteristic token and the rule information, and adding the business flow rule to a rule base.
In a specific embodiment of the present application, a json tag may be added to a fixed attribute field of a feature field, the json tag may be added to a variable attribute field and expressed in a map format, the entire feature field is used as a starting point, the json tag added to the attribute field is read layer by layer to a certain attribute field as an end point, and a feature access path of the attribute field is obtained in a manner of being separated by an english comma.
In practical application, a service flow request can specify a target object, and after receiving the service flow request, target attribute information corresponding to the target object can be loaded into a feature domain of a discrete parallel model to be used as a data source of a feature token; and one target object can be simultaneously circulated on a plurality of nodes in parallel, when a service circulation request is received, the node where the target object is located is used as a trigger starting point, after a certain circulation is successful, the target object can be circulated to other nodes in parallel or one node in series, and the node where the target object is located after circulation is used as the latest node.
Specifically, before receiving a service flow request, a feature domain and a feature token of the discrete parallel model need to be adjusted based on target attribute information of a target service, so that a target object corresponding to the target service can flow between nodes in the discrete parallel model.
In a specific embodiment of the application, a video content auditing service is taken as an example, video attribute information of a video to be audited corresponding to the video content auditing service is acquired, and the video attribute information is added into a feature domain of a discrete parallel model; and adjusting the feature token of the discrete parallel model according to the updated feature domain, and further generating a service flow rule based on the adjusted feature token and storing the service flow rule into a rule base.
The discrete parallel model is adjusted according to the target attribute information of the target service, so that the target object corresponding to the target service can be conveniently circulated between the nodes of the discrete parallel model in the follow-up process, and the target service can be processed based on the discrete parallel model.
Step 104: and determining a target service flow rule corresponding to the target node in a rule base based on the target service identification, wherein the rule base is generated based on a discrete parallel model.
Specifically, the rule base is a database containing the business flow rules of the target object, and after the feature token is generated based on the target attribute information of the target business, the business flow rules generated based on the feature token form the rule base; determining a target service in the rule base according to a target service identifier carried in the service flow request, and determining a target service flow rule corresponding to the target node of the discrete parallel model by the target service; the target business flow rule refers to a business flow rule corresponding to the target node.
In practical application, before determining the circulation of a target object among nodes of a discrete parallel model, a target node where the target object is located and which node can be circulated to are determined according to circulation information corresponding to the target object; after a target node where the target object is located is determined, a service flow rule corresponding to the target node needs to be obtained, specifically, the target service flow rule corresponding to the target service identification is searched in a rule base of the discrete parallel model according to the target service identification and the target node and is used as the target service flow rule of the target node, and then the target object in the target node is processed based on the determined target service flow rule.
In a specific embodiment of the present application, taking node a as an example, determining, in a rule base of a discrete parallel model, a service flow rule "corresponding to a service identifier" picture audit "according to the service identifier" picture audit "and a node a where a picture to be audited is located, and determining whether a picture size is greater than 100 k.
Target attribute information corresponding to the target object is analyzed based on the service flow rule, so that the discrete parallel model can process the target service in multiple dimensions.
In practical application, the specific method for determining the target service flow rule corresponding to the target node based on the target service identifier in the rule base comprises the following steps:
determining a service flow rule set based on the target service identification in a rule base;
and determining a target business flow rule corresponding to the target node in the business flow rule set.
For example, if the rule base includes a picture size determination rule and a picture definition determination rule, which are both picture audit rules, the picture size determination rule and the picture definition determination rule may form a service flow rule set.
In practical application, a rule base of the discrete parallel model can contain a plurality of service flow rule sets, and a target service flow set corresponding to a target service in the rule base can be determined based on a target service identifier in a service flow request; after the target service flow set is determined, a target service flow rule corresponding to the target node may be determined in a plurality of service flow rules of the target service flow set.
In a specific embodiment of the present application, taking the example that the target service identifier is video audit, the target service identifier "video audit" in the service flow request is determined; determining a video audit circulation rule set corresponding to the identifier based on the video audit identifier in a rule base of the discrete parallel model; and if the picture to be audited is determined to be in the node B, determining a video size auditing rule corresponding to the node B in the video auditing circulation rule set.
Step 106: and determining target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identification, wherein the feature domain is generated based on a discrete parallel model.
Specifically, after the target service flow rule and the target service identifier corresponding to the target node are determined, the target attribute information required by the target object under the target service when the target node flows can be determined according to the target service flow rule and the target service identifier.
In practical application, a feature domain of a discrete parallel model contains target attribute information corresponding to a target service, which attribute fields in the target attribute information are used for circulation of a target object at a target node can be determined based on a target service circulation rule, and a specific meaning corresponding to the attribute fields can be determined according to a target service identifier, for example, in a picture checking service, the target service circulation rule determines that circulation of a picture to be checked at the target node requires a picture definition attribute field, and a specific numerical value of the picture definition attribute field can be determined to be 480p based on the target service identifier.
In practical application, the method for determining the target attribute information corresponding to the target object in the feature domain according to the target service flow rule and the target service identifier comprises the following steps:
determining a target characteristic token in the target business circulation rule;
and determining target attribute information corresponding to the target object based on the target feature token and the target service identifier.
The target feature token refers to any one of a plurality of feature tokens in the target service circulation rule, for example, the target service circulation rule is that "the picture size is greater than 100k | | the picture definition is greater than 480 p", wherein "the picture size is greater than 100 k" and "the picture definition is greater than 480 p" are both feature tokens, a picture size field and a picture definition field can be determined when the picture to be checked circulates at the target node according to the target feature token, and the picture size 200k and the picture definition 480p of the picture to be checked can be obtained in the feature domain according to the target service identifier.
In a specific embodiment of the present application, taking a video review service as an example, a service flow rule of a video to be reviewed at a node C is "the video is not in an MP4 format | | | video in a video list"; determining the feature tokens in the traffic flow rule as "video is not in MP4 format" and "video is in video list"; and determining a video format field and a video range field in the feature domain according to the feature token, and acquiring video format information (AVI) corresponding to the video format field and video range information (in a video list) corresponding to the video range field in the feature domain according to the service identifier (video audit).
The target attribute information corresponding to the target object is determined in the feature domain according to the target service flow rule and the target service identification, so that the target attribute information corresponding to the target object can be conveniently analyzed based on the target service flow rule subsequently, and a flow result is obtained.
Step 108: and analyzing the target attribute information based on the target service flow rule to obtain a flow result.
Specifically, after the target attribute information is determined, the target attribute information may be analyzed by the target service flow rule, so as to obtain a flow result of the target object in the discrete parallel model.
In practical application, the method for obtaining the circulation result by analyzing the target attribute information based on the target service circulation rule comprises the following steps:
determining a feature token and an operation identifier in the target service flow rule;
and analyzing the target attribute information according to the feature token and the operation identifier to obtain a circulation result.
The operation identifier refers to an operation symbol between the feature tokens in the service flow rule, such as an equal sign, an unequal sign, a bracket and the like; the feature token is to generate an attribute information determination rule according to the target attribute information, for example, a picture state is a to-be-audited state, a picture size is greater than 100k, and the like; the target attribute information is processed according to the feature token and the operation identifier determined in the target service flow rule, and a flow result of the target object can be obtained, wherein the flow result refers to flow information obtained by analyzing the target attribute information according to the target service flow rule, for example, it is determined that a picture to be checked flows from a first audit node to a second audit node.
In a specific embodiment of the application, for example, a picture auditing service is taken as an example, it is determined that a picture to be audited is at a node C and a service flow rule corresponding to the node C is that "the picture size is greater than 20k & & the picture definition is greater than 480 p"; determining feature tokens in the service flow rule as 'picture size is larger than' and 'picture definition is larger than 480 p' and determining operation identification as '&'; and obtaining a circulation result of the picture to be audited in the discrete parallel model according to the determined feature token and the operation identifier.
In practical application, the specific method for obtaining the circulation result by analyzing the target attribute information according to the feature token and the operation identifier comprises the following steps:
determining a circulation result to be processed according to the feature token and the target attribute information;
and calculating a circulation result based on the circulation result to be processed and the operation identifier.
The to-be-processed circulation result refers to a calculation result of a target feature token obtained by calculation according to target attribute information and the target feature token, for example, a service circulation rule is that "the picture size is greater than 100k | | the picture definition is greater than or equal to 480 p", attribute information obtained in a feature domain is that "the picture size is 10 k" and "the picture definition is 480 p", calculation results of the feature token obtained according to the attribute information and the service circulation rule are respectively "no" and "yes", that is, the picture size is smaller than the value 100k of the feature token in the service circulation rule, and the picture definition 480p is equal to 480p in the service circulation rule; after the circulation result to be processed is determined, the circulation result of the target object can be obtained through calculation according to the operation identification and the circulation result to be processed.
In a specific embodiment of the application, taking a video review service as an example, determining a service flow rule of a review node where a picture to be reviewed is located as "a video is in an MP4 format | | video in a video list", determining a feature token "the video is in an MP4 format" and "the video is in the video list" in the service flow rule, and calculating an identifier "| |"; determining that the calculation results of the feature token are yes and no respectively according to attribute information 'video format MP 4' and 'video is not in a video list' acquired in the feature field; and (3) obtaining a circulation result according to the characteristic token and the operation identifier, | | | | to circulate the picture to be audited to the secondary audit node.
In practical application, the specific method for determining the circulation result to be processed according to the feature token and the target attribute information comprises the following steps:
determining a target feature token and a variable identifier in the target feature token;
determining target feature attribute information corresponding to the target feature token in the target attribute information based on the variable identification;
and determining a target circulation to be processed result of the target characteristic token according to the target characteristic attribute information, the calculation identifier and the calculation threshold in the target characteristic token.
The variable identification refers to an identification of an attribute field needing to be determined by a target object in a circulation process, for example, if a feature token is 'picture size less than 100 k', the variable identification is 'picture size', the picture size field can be determined in target attribute information based on the variable identification, in practical application, when a discrete parallel model is a colored petri net, the variable identification can be color information bound by the feature token, and the target feature attribute information can be determined in a feature domain through the color information; the target feature attribute information refers to attribute information corresponding to the variable identifier in the target attribute information, for example, the attribute information corresponding to the variable identifier "picture size" is "picture size 50 k"; the target feature token is any one of the feature tokens in the traffic flow rule, and the target feature token includes a calculation identifier and a calculation threshold, where the calculation identifier refers to a calculation symbol in the target feature token, such as an equal number, an unequal number, or, and the like, and the calculation threshold refers to a threshold set in the target feature token, for example, "100 k" in "100 k" of the feature token is a calculation threshold; the target circulation to be processed result is a calculation result which is obtained according to the target characteristic attribute information and the target characteristic token and corresponds to the target characteristic token.
In a specific embodiment of the present application, taking a video review service as an example, a service flow rule of an audit node where a picture to be reviewed is located is "a video in a video list in an MP4 format |; determining that the target feature token is in a video format (MP 4 format), identifying the variable as the video format, and determining that the attribute information is in the video format as AVI in the target attribute information according to the variable identification; if the calculation identifier in the target feature token is determined to be "the calculation threshold is" MP4 format ", the calculation result of the target feature token is obtained as" no "according to the attribute information" video format is AVI ", the calculation identifier" and the calculation threshold "MP 4 format".
In practical application, the specific method for calculating the circulation result based on the circulation result to be processed and the operation identifier comprises the following steps:
determining an operation sequence according to the operation identification and a preset operation priority;
and calculating a circulation result based on the operation sequence, the operation identification and the circulation result to be processed.
The preset operation priority refers to a priority determined according to the operation identifier, for example, when the operation identifier is a bracket, the operation needs to be performed preferentially on the content in the bracket, and then, the multiplication and division calculation is performed first and then the addition and subtraction calculation is performed.
Specifically, after the target service flow rule is determined, an operation sequence needs to be determined according to an operation identifier in the target service flow rule, that is, the operation sequence is determined based on the operation rule corresponding to the operation rule, and then calculation is performed in sequence based on the operation sequence, the operation identifier and the flow result to be processed, so that a final calculation result is obtained.
Further, in order to improve the operation efficiency and efficiently analyze the target attribute information based on the target service flow rule, the flow result of the target object may be obtained by gradually calculating the to-be-processed flow result corresponding to the feature token based on the operation sequence and the operation identifier, for example, the service flow rule is "feature token 1& & & (feature token 2| | | | feature token 3)", and the operation sequence is: calculating a feature token 1 to obtain a to-be-processed calculation result r1, then calculating a feature token 2 in parentheses to obtain a calculation result r2, if the calculation result r2 of the feature token 2 is false, determining that the calculation result in parentheses is false, determining that the circulation result of the target object can be r2 without performing on the feature token 3, and if the calculation result r2 of the feature token 2 is true, calculating a calculation result r3 of the feature token 3 and identifying a mark "!according to the operation! "reverse r3 to obtain r-3, determine the calculation result ri in brackets according to r2 and r-3, and obtain the final circulation result based on ri and r 1.
In practical applications, the service flow rule may include an operation of adjusting target attribute information corresponding to a target object, such as assignment, for example, assigning "not-approved" status information of an audit picture to "to be audited", and then after obtaining a flow result, the corresponding target attribute information in the feature domain needs to be updated, so that the information in the feature domain is the latest attribute information, and specifically, after analyzing the target attribute information based on the target service flow rule to obtain the flow result, the method further includes:
and updating the target attribute information in the feature domain based on the circulation attribute information in the circulation result.
The flow attribute information refers to attribute information which changes in the flow process, for example, the audit state of a picture to be audited is changed from an 'non-audit state' to a 'to-be-audited state' based on a service flow rule in the flow process, and then the audit state information is determined to be the flow attribute information; and adjusting the corresponding attribute information in the feature domain according to the circulation attribute information determined in the circulation result, and finishing the updating of the feature domain.
Specifically, before adjusting the target attribute information in the feature domain, the current feature domain may be copied as an old version of the feature domain, and then the feature domain is adjusted, including adjusting the service content information, the service rule information, and the service flow information as a new version of the feature domain; after a certain flow is completed, the new version of the feature domain can be copied as the old version of the feature domain of the current flow.
In practical application, after analyzing the target attribute information based on the target service flow rule to obtain a flow result, the method further includes:
and processing the target object in the target node based on the circulation result.
In practical applications, the flow result includes processing information for the target object, for example, the processing information may be to flow the target object from the first audit node to the second audit node, may be to end the flow and return the flow result to the client, and the like.
In a specific embodiment of the present application, taking a picture auditing service as an example, a circulation result of a picture to be audited at a first audit node is determined, and processing information in the circulation result is determined as "circulation of the first audit node to a second audit node"; and transferring the picture to be audited to the secondary audit node according to the processing information.
In the service processing method provided by the embodiment of the application, the target service flow rule corresponding to the target node is determined based on the target service identifier, so that the specific change of each rule can be conveniently and visually known; target attribute information of the target object is analyzed based on the target service flow rule to obtain a flow result, so that multi-aspect analysis of the target attribute information is realized, and the comprehensiveness of auditing is improved.
The following describes the service processing method further by taking the application of the service processing method provided by the present application in reviewing and auditing services as an example, with reference to fig. 2. Fig. 2 shows a processing flow chart of a service processing method applied to review service according to an embodiment of the present application, which specifically includes the following steps:
step 202: receiving a service flow request, and determining a target service identifier of a target object carried in the service flow request.
In the embodiment, the discrete parallel model is adjusted based on the audit requirement of the user on the review resources, specifically, the attribute information corresponding to the review service is obtained, and the obtained attribute information is added into the feature domain of the discrete parallel model; and updating or creating a feature token based on the updated feature domain, and adding the service flow rule generated based on the feature token into a rule base added with the discrete parallel model.
Step 204: and determining a business flow rule set in a rule base based on the target business identification.
In this embodiment, a comment auditing service flow rule set corresponding to the comment auditing service identifier is determined in a rule base corresponding to the discrete parallel model according to the comment auditing service identifier.
Step 206: and determining a target business flow rule corresponding to the target node in the business flow rule set.
In this embodiment, a target review service circulation rule corresponding to the review node where the review to be reviewed is located is determined in the review service circulation rule.
Step 208: and determining a target characteristic token in the target business flow rule.
In this embodiment, the target comment auditing service flow rule is that "comment resource state ═ to-be-audited state & & comment character total number <15 characters"; and determining that the feature tokens in the target comment auditing business flow rule are respectively a comment resource state which is a to-be-audited state and a comment character total number which is less than 15 characters.
Step 210: and determining target attribute information corresponding to the target object based on the target feature token and the target service identifier.
In this embodiment, a comment attribute information set corresponding to a comment to be reviewed is determined in a feature domain according to a feature token, where "comment resource state is to be reviewed", "comment character total number is less than 15 characters", and a comment review service identifier.
Step 212: determining a variable identification in the target feature token, and determining target feature attribute information corresponding to the target feature token in the target attribute information based on the variable identification.
In this embodiment, the variable identifier that determines that the feature token "comment resource state is to be audited" is the "comment resource state", and the variable identifier that determines that the feature token "comment total number of characters <15 characters" is the "comment character total number"; and according to the variable identifier 'comment resource state', determining attribute information corresponding to the comment to be audited in the comment attribute information set as 'comment resource state is not audited', and according to the variable identifier 'comment character total number', determining attribute information corresponding to the comment to be audited in the comment attribute information set as 'comment character total number 5'.
Step 214: and obtaining a target circulation to be processed result of the target characteristic token according to the target characteristic attribute information, the calculation identifier and the calculation threshold in the target characteristic token.
In this embodiment, it is determined that a calculation identifier in the feature token "comment resource state is equal to the to-be-audited state" is equal to "a calculation threshold value is equal to" the to-be-audited state ", and a to-be-processed circulation result of the feature token" comment resource state is equal to the to-be-audited state "is calculated and obtained as an assignment of the comment resource state of the to-be-audited comment to the" to-be-audited state "; determining that the calculation identifier of the feature token 'total number of comment characters <15 characters' is '15 characters', and calculating that the to-be-processed circulation result of the feature token 'total number of comment characters <15 characters' is 'yes', namely the total number of comment characters is less than 15 characters.
Step 216: and determining an operation identifier in the target feature token, and calculating a circulation result according to the operation identifier and a circulation processing result.
In this embodiment, it is determined that the operation identifier in the target comment auditing service flow rule is "&", the operation order is determined according to the operation identifier and the calculation priority of the operation identifier as that the feature token "comment resource state is to be audited" and the feature token "comment resource state is to be audited", and finally, "&" between two feature tokens is calculated again, and a flow result is obtained as "yes", and flow information in the flow result is that the comment to be audited is transferred from the auditing node to the second auditing node.
Step 218: and updating the target attribute information in the feature domain based on the flow attribute information in the flow result, and processing the target object in the target node according to the flow result.
In the embodiment, the flow attribute information in the flow result is determined to be 'the state of being not checked is modified into the state to be checked', and the comment resource state of the comment to be checked in the feature domain is modified into the state to be checked according to the flow attribute information; and circulating the comments to be audited to a second audit transition according to circulation information in the circulation result.
In the service processing method provided by the embodiment of the application, the target service flow rule corresponding to the target node is determined based on the target service identifier, so that the specific change of each rule can be conveniently and visually known; target attribute information of the target object is analyzed based on the target service flow rule to obtain a flow result, so that multi-aspect analysis of the target attribute information is realized, and the comprehensiveness of auditing is improved.
Corresponding to the above method embodiment, the present application further provides an embodiment of a service processing apparatus, and fig. 3 shows a schematic structural diagram of a service processing apparatus provided in an embodiment of the present application. As shown in fig. 3, the apparatus includes:
a receiving module 302, configured to receive a service flow request, where the service flow request carries a target service identifier of a target object;
a first determining module 304, configured to determine a target service flow rule corresponding to the target node based on the target service identifier in a rule base, where the rule base is generated based on a discrete parallel model;
a second determining module 306, configured to determine, according to the target service flow rule and the target service identifier, target attribute information corresponding to the target object in a feature domain, where the feature domain is generated based on a discrete parallel model;
and the analysis module 308 is configured to analyze the target attribute information based on the target service flow rule to obtain a flow result.
In a specific embodiment of the present application, the apparatus further includes a receiving submodule configured to:
receiving target attribute information of a target service, and generating a feature domain according to the target attribute information;
and creating a feature token based on the feature domain, and generating a rule base according to the feature token.
Optionally, the first determining module 304 is further configured to:
determining a service flow rule set based on the target service identification in a rule base;
and determining a target business flow rule corresponding to the target node in the business flow rule set.
Optionally, the second determining module 306 is further configured to:
determining a target characteristic token in the target business circulation rule;
and determining target attribute information corresponding to the target object based on the target feature token and the target service identifier.
Optionally, the parsing module 308 is further configured to:
determining a feature token and an operation identifier in the target service flow rule;
and analyzing the target attribute information according to the feature token and the operation identifier to obtain a circulation result.
Optionally, the parsing module 308 is further configured to:
determining a circulation result to be processed according to the feature token and the target attribute information;
and calculating a circulation result based on the circulation result to be processed and the operation identifier.
Optionally, the parsing module 308 is further configured to:
determining a target feature token and a variable identifier in the target feature token;
determining target feature attribute information corresponding to the target feature token in the target attribute information based on the variable identification;
and determining a target circulation to be processed result of the target characteristic token according to the target characteristic attribute information, the calculation identifier and the calculation threshold in the target characteristic token.
Optionally, the parsing module 308 is further configured to:
determining an operation sequence according to the operation identification and a preset operation priority;
and calculating a circulation result based on the operation sequence, the operation identification and the circulation result to be processed.
Optionally, the apparatus further comprises an update module configured to:
and updating the target attribute information in the feature domain based on the circulation attribute information in the circulation result.
Optionally, the apparatus further comprises a processing module configured to:
and processing the target object in the target node based on the circulation result.
The service processing device comprises a receiving module and a processing module, wherein the receiving module receives a service flow request, and the service flow request carries a target service identifier of a target object; the first determining module is used for determining a target service circulation rule corresponding to the target node in a rule base based on the target service identification, wherein the rule base is generated based on a discrete parallel model; the second determining module is used for determining target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identifier, wherein the feature domain is generated based on a discrete parallel model; and the analysis module is used for analyzing the target attribute information based on the target service flow rule to obtain a flow result. The business processing device obtains the circulation result based on the target business circulation rule, realizes multi-aspect analysis of the target attribute information corresponding to the target object based on the target business circulation rule, and further realizes multi-dimensional analysis of the target business.
The foregoing is a schematic scheme of a service processing apparatus according to this embodiment. It should be noted that the technical solution of the service processing apparatus and the technical solution of the service processing method belong to the same concept, and details that are not described in detail in the technical solution of the service processing apparatus can be referred to the description of the technical solution of the service processing method.
Fig. 4 shows a block diagram of a computing device 400 provided according to an embodiment of the present application. The components of the computing device 400 include, but are not limited to, a memory 410 and a processor 420. Processor 420 is coupled to memory 410 via bus 430 and database 450 is used to store data.
Computing device 400 also includes access device 440, access device 440 enabling computing device 400 to communicate via one or more networks 460. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 440 may include one or more of any type of network interface (e.g., a Network Interface Card (NIC)) whether wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the application, the above-described components of computing device 400 and other components not shown in FIG. 4 may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 4 is for purposes of example only and is not limiting as to the scope of the present application. Those skilled in the art may add or replace other components as desired.
Computing device 400 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 400 may also be a mobile or stationary server.
Wherein, the processor 420 implements the steps of the service processing method when executing the computer instructions.
The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device and the technical solution of the service processing method belong to the same concept, and details that are not described in detail in the technical solution of the computing device can be referred to the description of the technical solution of the service processing method.
An embodiment of the present application further provides a computer readable storage medium, which stores computer instructions, and the computer instructions, when executed by a processor, implement the steps of the service processing method as described above.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the service processing method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the service processing method.
The foregoing description of specific embodiments of the present application has been presented. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The preferred embodiments of the present application disclosed above are intended only to aid in the explanation of the application. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the application and its practical applications, to thereby enable others skilled in the art to best understand and utilize the application. The application is limited only by the claims and their full scope and equivalents.
Claims (14)
1. A service processing method is characterized in that a target node applied to a discrete parallel model comprises the following steps:
receiving a service flow request, wherein the service flow request carries a target service identifier of a target object;
determining a target service circulation rule corresponding to the target node in a rule base based on the target service identification, wherein the rule base is generated based on a discrete parallel model;
determining target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identification, wherein the feature domain is generated based on a discrete parallel model;
and analyzing the target attribute information based on the target service flow rule to obtain a flow result.
2. The traffic processing method of claim 1, further comprising, before receiving the traffic flow request:
receiving target attribute information of a target service, and generating a feature domain according to the target attribute information;
and creating a feature token based on the feature domain, and generating a rule base according to the feature token.
3. The traffic processing method according to claim 1, wherein determining the target traffic flow rule corresponding to the target node based on the target traffic identifier in a rule base comprises:
determining a service flow rule set based on the target service identification in a rule base;
and determining a target business flow rule corresponding to the target node in the business flow rule set.
4. The service processing method according to claim 1, wherein determining the target attribute information corresponding to the target object in the feature domain according to the target service flow rule and the target service identifier comprises:
determining a target characteristic token in the target business circulation rule;
and determining target attribute information corresponding to the target object based on the target feature token and the target service identifier.
5. The service processing method of claim 1, wherein parsing the target attribute information based on the target service flow rule to obtain a flow result comprises:
determining a feature token and an operation identifier in the target service flow rule;
and analyzing the target attribute information according to the feature token and the operation identifier to obtain a circulation result.
6. The service processing method according to claim 5, wherein analyzing the target attribute information according to the feature token and the operation identifier to obtain a circulation result comprises:
determining a circulation result to be processed according to the feature token and the target attribute information;
and calculating a circulation result based on the circulation result to be processed and the operation identifier.
7. The traffic processing method according to claim 6, wherein determining a to-be-processed flow result according to the feature token and the target attribute information includes:
determining a target feature token and a variable identifier in the target feature token;
determining target feature attribute information corresponding to the target feature token in the target attribute information based on the variable identification;
and determining a target circulation to be processed result of the target characteristic token according to the target characteristic attribute information, the calculation identifier and the calculation threshold in the target characteristic token.
8. The service processing method according to claim 6, wherein calculating a circulation result based on the circulation result to be processed and the operation identifier includes:
determining an operation sequence according to the operation identification and a preset operation priority;
and calculating a circulation result based on the operation sequence, the operation identification and the circulation result to be processed.
9. The service processing method according to any one of claims 1 to 8, wherein after parsing the target attribute information based on the target service flow rule to obtain a flow result, further comprising:
and updating the target attribute information in the feature domain based on the circulation attribute information in the circulation result.
10. The service processing method according to any one of claims 1 to 8, wherein after parsing the target attribute information based on the target service flow rule to obtain a flow result, further comprising:
and processing the target object in the target node based on the circulation result.
11. The business processing method of any one of claims 1 to 8, wherein the discrete parallel model is a model composed of nodes, transitions, and connection arcs between the nodes and the transitions, a target object flows among the nodes of the discrete parallel model, each node or transition has a corresponding business flow rule, and the flow direction of the target object between the nodes and the libraries of the discrete parallel model is determined based on the business flow rules;
the feature domain includes target attribute information corresponding to the target service, where the target attribute information includes at least one of service content information, service rule information, and service flow information corresponding to the target service.
12. A service processing apparatus, applied to a target node of a discrete parallel model, comprising:
the system comprises a receiving module, a service flow processing module and a service flow processing module, wherein the receiving module is configured to receive a service flow request, and the service flow request carries a target service identifier of a target object;
a first determining module configured to determine a target service flow rule corresponding to the target node based on the target service identifier in a rule base, wherein the rule base is generated based on a discrete parallel model;
the second determining module is configured to determine target attribute information corresponding to the target object in a feature domain according to the target service flow rule and the target service identifier, wherein the feature domain is generated based on a discrete parallel model;
and the analysis module is configured to analyze the target attribute information based on the target service flow rule to obtain a flow result.
13. A computing device comprising a memory, a processor, and computer instructions stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-11 when executing the computer instructions.
14. A computer-readable storage medium storing computer instructions, which when executed by a processor, perform the steps of the method of any one of claims 1 to 11.
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