CN117391856A - Transaction data processing method, device, computer equipment and storage medium - Google Patents
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Abstract
The present application relates to the field of big data technology, and in particular, to a transaction data processing method, apparatus, computer device, storage medium, and computer program product. The method comprises the following steps: acquiring initial transaction data; acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching; screening initial transaction data according to the group of target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data; matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network; and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes. By adopting the method, the transaction data processing efficiency can be improved, and the accuracy of the classification result can be improved.
Description
Technical Field
The present application relates to the field of big data technology, and in particular, to a transaction data processing method, apparatus, computer device, storage medium, and computer program product.
Background
Under the age of big data information, data processing has new meaning, and the generation of digital technologies such as cloud computing, data processing becomes a technical means of data and information. With the high-speed development of Internet economy, the generated information is huge, a rule engine is required to process massive data, and the current rule engine is widely applied in various industries.
In the conventional technology, a rule engine matches a huge amount of target data with rules.
However, the current rule matching engine causes inefficiency in data processing due to the large amount of data generated being processed to match the rules.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a transaction data processing method, apparatus, computer device, computer readable storage medium, and computer program product that can improve the efficiency of transaction data processing.
In a first aspect, the present application provides a transaction data processing method, including:
Acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening the initial transaction data according to the group of the target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
according to the sequence of each node in the target rule matching network, matching each node in the target rule matching network of the target transaction data;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In one embodiment, before obtaining the target rule matching network and the rule processing range information, the method further includes:
receiving a rule configuration instruction;
determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction;
taking each matching condition as a node, and determining a connecting line between the nodes based on the sequence of the matching conditions;
and determining a target rule matching network according to the nodes and the connection lines.
In one embodiment, each matching condition is taken as a node, and the method comprises the following steps:
Acquiring an initial rule matching network;
matching the matching condition with each node in the initial rule matching network;
and when the node corresponding to the matching condition exists in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node.
In one embodiment, obtaining the classification result corresponding to the target transaction data based on the successfully matched node and the connection line of the successfully matched node includes:
determining an activated rule based on the successfully matched node and the connection line of the successfully matched node;
and determining a classification result corresponding to the target transaction data based on the activated rule.
In one embodiment, obtaining initial transaction data includes:
acquiring initial transaction data and storing the initial transaction data to a message queue;
receiving an initial transaction data subscription request, and configuring subscription information of initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
In one embodiment, after obtaining the classification result corresponding to the target transaction data based on the successfully matched node and the connection line of the successfully matched node, the method includes:
And outputting a classification result corresponding to the target transaction data.
In a second aspect, the present application also provides a transaction data processing apparatus, including:
the data acquisition module is used for acquiring initial transaction data;
the rule processing range acquisition module is used for acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
the screening module is used for screening the initial transaction data according to the community of the target user matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
the matching module is used for matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network;
and the result generation module is used for obtaining the classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
Acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening initial transaction data according to the group of target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
according to the sequence of each node in the target rule matching network, matching each node in the target transaction data target rule matching network;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening initial transaction data according to the group of target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
According to the sequence of each node in the target rule matching network, matching each node in the target transaction data target rule matching network;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:
acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening initial transaction data according to the group of target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
according to the sequence of each node in the target rule matching network, matching each node in the target transaction data target rule matching network;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
The transaction data processing method, the device, the computer equipment, the storage medium and the computer program product are characterized in that initial transaction data, a target rule matching network and rule processing range information are acquired, wherein the rule processing range information comprises a group of target users participating in rule matching and occurrence time of the initial transaction data; then screening the initial transaction data based on the group of the target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data; matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network; and finally, obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes. The target transaction data is obtained by screening the initial transaction data based on the rule processing range information, so that the transaction data processing amount of the target rule matching network data is reduced, and the transaction data processing efficiency is improved; the adoption of the target rule matching network to process the transaction data also improves the efficiency of transaction data processing, and simultaneously improves the accuracy of classification results corresponding to the transaction data.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.
FIG. 1 is an application environment diagram of a transaction data processing method in one embodiment;
FIG. 2 is a flow chart of a transaction data processing method according to one embodiment;
FIG. 3 is a flow diagram of one embodiment prior to obtaining a target rule matching network and rule processing scope information;
FIG. 4 is a schematic flow chart of using each matching condition as a node in one embodiment;
FIG. 5 is a flowchart of a method for obtaining classification results corresponding to target transaction data according to an embodiment;
FIG. 6 is a flow diagram of acquiring initial transaction data in one embodiment;
FIG. 7 is a block diagram of a transaction data processing device in one embodiment;
fig. 8 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The transaction data processing method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The server 104 obtains initial transaction data; acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching; screening initial transaction data according to the group of target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data; according to the sequence of each node in the target rule matching network, matching each node in the target transaction data target rule matching network; screening the initial transaction data based on the rule processing range information to obtain target transaction data; matching the target transaction data with each node in the target rule matching network; and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
In an exemplary embodiment, as shown in fig. 2, a transaction data processing method is provided, which is exemplified by the application of the method to a rule matching engine, and the rule matching engine is located in the server 104 in fig. 1, and includes the following steps S202 to S206. Wherein:
step S202, obtaining initial transaction data.
Wherein the initial transaction data may include basic information data and behavior data of the user. Wherein the behavioral data may refer to a user transaction flow message.
Optionally, the transaction data acquisition system acquires the user transaction flow messages from each transaction system, the transaction data acquisition system sends a large number of user transaction flow messages to the rule matching engine, and the rule matching engine acquires a large number of user transaction flow messages, namely initial transaction data.
Step S204, a target rule matching network and rule processing range information are obtained, wherein the rule processing range comprises the group of target users participating in rule matching and the occurrence time of initial transaction data.
The rule matching network is a network formed by arranging all nodes according to certain conditions, and all nodes of the rule matching network are all rule matching conditions. The rule processing range information refers to limit information of rule processing, and the rule processing range information can comprise the occurrence time of the group of target users participating in rule matching and initial transaction data; other conditions that limit the initial transaction data are also possible. The rule processing range information can be adjusted and changed according to actual conditions.
Optionally, before the rule matching engine obtains the target rule matching network and the rule processing range information, the rule matching conditions generate a rule matching condition set, and the rule matching conditions in the set are arranged and combined according to a certain condition to obtain the target matching network. The rule configuration background deploys matching rules and rule processing range information, and sends the matching rules and the rule processing range information to the rule matching engine, so that the rule matching engine obtains the generated target matching network and the rule processing range information, and the rule processing range information can comprise the occurrence time of the target user belonging to the rule matching and the occurrence time of initial transaction data.
Step S206, screening the initial transaction data according to the community of the target user matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data.
Optionally, the rule matching engine judges and analyzes the initial transaction data based on the group to which the target user participating in rule matching belongs and the occurrence time of the initial transaction data, judges whether the initial transaction data belongs to a rule processing range, processes the initial transaction information when the initial transaction data belongs to the rule processing range, judges whether the user information contained in the initial transaction information belongs to the group to which the target user participating in rule matching, can also judge whether the occurrence time of the initial transaction data belongs to a target time period, does not limit the judging sequence of the group to which the target user participating in rule matching belongs and the occurrence time of the initial transaction data, can firstly judge whether the user information contained in the initial transaction information belongs to the group to which the target user participating in rule matching belongs, and can also firstly judge whether the occurrence time of the initial transaction data belongs to the target time period; then further counting and analyzing the initial transaction data; when the initial transaction data does not accord with the conditions of the group of the target users matched with the participation rule and the occurrence time of the initial transaction data, eliminating the initial transaction which does not accord with the conditions; thereby obtaining target transaction data.
Step S208, according to the sequence of the nodes in the target rule matching network, the nodes in the target rule matching network of the target transaction data are matched.
Wherein each node in the target rule matching network refers to a matching condition with executable judgment logic.
Optionally, the target transaction data obtained by the rule matching engine is sent to the obtained target rule matching network. According to the sequence of each node in the target rule matching network, the target transaction data are matched with each node in the target rule matching network one by one. The target transaction data traverses the target rule matching network from a root node, also called an entry node, and sequentially executes each node in the target rule matching network.
Optionally, each node in the target rule matching network has a corresponding storage space, and when the judging logic is executed, that is, when matching with the matching condition, the storage space stores an execution result (matching judging result) correspondingly, and the execution result (matching judging result) can be read when the subsequent node executes the matching judgment.
Step S210, based on the successfully matched nodes and the connection lines of the successfully matched nodes, a classification result corresponding to the target transaction data is obtained.
The connection of the nodes can be the sequence of the nodes, and the nodes are sequentially matched according to the sequence of the connection.
Optionally, counting all the matched nodes after the connection traversal of the nodes is completed, and obtaining classification result data corresponding to the target transaction data based on the successfully matched nodes and the connection of the successfully matched nodes.
In the transaction data processing method, initial transaction data, a target rule matching network and rule processing range information are acquired, wherein the rule processing range information comprises a group of target users participating in rule matching and occurrence time of the initial transaction data; then screening the initial transaction data based on the group of the target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data; matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network; and finally, obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes. The target transaction data is obtained by screening the initial transaction data based on the rule processing range information, so that the transaction data processing amount of the target rule matching network data is reduced, and the transaction data processing efficiency is improved; the adoption of the target rule matching network to process the transaction data also improves the efficiency of transaction data processing, and simultaneously improves the accuracy of classification results corresponding to the transaction data.
In an exemplary embodiment, as shown in fig. 3, before the target rule matching network and the rule processing range information are acquired, steps S302 to S306 are further included. Wherein:
step S302, a rule configuration instruction is received.
The rule configuration instruction is an instruction of an arrangement mode in the target matching network according to the characteristics of the rule. The specific representation of the matching conditions may be included, as may the order of the matching conditions.
Optionally, the rule matching engine generates the configured rule before receiving the rule configuration instruction issued by the rule configuration background. For each preset initial rule, acquiring corresponding rule information of a field limiting initial data from the initial rule; setting rules of fields corresponding to the rule information in the combined initial data as the rule information; thereby generating a rule of configuration. And the matching engine receives the rule configuration instruction.
Step S304, based on the rule configuration instruction, each matching condition corresponding to the rule and the sequence of the matching conditions are determined.
Optionally, the rule matching engine determines each matching condition corresponding to the rule and the sequence of the matching conditions based on the received rule configuration instruction. The rule configuration instruction carries matching condition information and matching condition sequence information, for example, the matching condition information is related to accounts, including that 'account consumption flow is more than 1000', 'account type is employee', 'account location is city A', the matching condition sequence information is that 'account location is city A' is matched firstly, and then the matching condition is that 'account consumption flow is more than 1000'; and finally, matching under the condition of 'account type is employee'.
And step S306, taking each matching condition as a node, and determining the connection line between each node based on the sequence of the matching conditions.
The nodes may include root nodes, intermediate nodes, leaf nodes, and the like.
Optionally, the rule matching engine takes each matching condition as a node, and takes three matching conditions of "account consumption flowing water is more than 1000" "" account type is employee "" "account location is city A" ", as three nodes of the target matching network, and determines a connecting line between the nodes based on the sequence of the matching conditions, namely, the node 1 is" account location is city A "", the node 2 is connected, and the account consumption flowing water is more than 1000"; node 2 "accounts consumption flowing water is greater than 1000" connect node 3 "accounts type is employee.
Step S308, determining a target rule matching network according to the nodes and the connection lines.
Optionally, the rule matching engine determines the target rule matching network according to the specific content of the nodes and the distribution sequence of the nodes.
In this embodiment, by generating the target rule matching network, it is not necessary to develop separately in each matching process, and it is possible to achieve reuse of the matching process using the target rule matching network.
In an exemplary embodiment, as shown in fig. 4, each matching condition is taken as a node, including steps S402 to S406. Wherein:
step S402, an initial rule matching network is obtained.
Optionally, the rule matching engine obtains an initial rule matching network, and forms a target rule matching network by adding nodes into the initial rule matching network.
And step S404, matching the matching condition with each node in the initial rule matching network.
Optionally, the rule matching engine matches the matching condition with each node in the initial rule matching network, and determines that the matching condition is a node type in the initial rule matching network according to the specific content of the matching condition, for example, determines that the matching condition is a root node, an intermediate node or a leaf node in the initial rule matching network according to the specific content of the matching condition; and determining the sequence between the matching conditions according to the specific content of each matching condition and the rule configuration instruction.
In step S406, when there is a node corresponding to the matching condition in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node.
The storage content of the sharing node can be read and used by a plurality of subsequent nodes.
Optionally, when a node corresponding to the matching condition exists in the initial rule matching network, the rule matching engine takes the node successfully matched with the matching condition as a shared node. For example, the matching condition content is "account consumption flowing water is greater than 1000", the node 1 with the matching condition content is connected with the node 2 with the matching condition content of "account type is employee", and is also connected with the node 3 with the matching condition content of "account place is city a", when the node corresponding to the three matching conditions of "account consumption flowing water is greater than 1000", "account type is employee", "account place is city a" exists in the initial rule matching network, and the matching is successful, the node 1 with the matching condition content of "account consumption flowing water is greater than 1000" can be used as a sharing node, and the matching condition of the sharing node 1 can be used by the sharing node 2 and the node 3.
In this embodiment, the node successfully matched with the matching condition is used as the sharing node, so that the effect of realizing node data sharing and reducing data storage can be achieved.
In an exemplary embodiment, as shown in fig. 5, based on the node successfully matched and the connection line of the node successfully matched, a classification result corresponding to the target transaction data is obtained, which includes steps S502 to S504. Wherein:
Step S502, determining an activated rule based on the successfully matched node and the connection line of the successfully matched node.
Optionally, the target transaction data is screened and propagated through a target rule matching network, the rule matching engine determines an activated rule based on the successfully matched nodes and the connection lines of the successfully matched nodes, and the rule is activated when all the nodes and the connection lines between the nodes are matched.
Step S504, determining a classification result corresponding to the target transaction data based on the activated rule.
Optionally, the rule matching engine determines a classification result corresponding to the target transaction data based on the activated rule, and records a matching path in the rule matching engine and stores the matching path in the storage system.
In the embodiment, by activating the rule in the target rule matching network, the target transaction data can be accurately and efficiently classified and matched.
In one exemplary embodiment, as shown in FIG. 6, initial transaction data is obtained, including steps S602 through S604. Wherein:
step S602, obtain the initial transaction data, and store the initial transaction data to the message queue.
Optionally, the asynchronous message queue subscribes to a large amount of initial transaction data of the order receiving system and stores the initial transaction data to the message queue. Message queues may employ a DEA event driven message queue, which is a distributed asynchronous architecture mode that is often used to build highly scalable applications. It is of course also suitable for small applications, complex applications and applications of relatively large scale. This architecture mode consists of a series of highly decoupled components that receive and process events asynchronously.
Step S604, receiving an initial transaction data subscription request and configuring subscription information of initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
Optionally, the rule matching engine receives an initial transaction data subscription request and configures subscription information for the initial transaction data based on the initial transaction data subscription request. When the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data; when no initial transaction information is present in the message queue, no subscription information is generated.
In this embodiment, the throughput and response speed of the rule matching engine can be improved by acquiring the initial transaction data from the message queue based on the subscription information of the initial transaction data.
In an exemplary embodiment, after obtaining the classification result corresponding to the target transaction data based on the successfully matched node and the connection line of the successfully matched node, the method includes:
and outputting a classification result corresponding to the target transaction data.
Optionally, the rule matching engine outputs a classification result corresponding to the target transaction data and sends the classification result to the message platform, and the message platform sends corresponding information to the user terminal according to the content of the classification result according to the message sending request of the rule matching engine, and the corresponding content can be sent to the user terminal in a form of a short message, a mail or the like, and the sending process can be batch or one by one, and the sending time can be either timing sending or real-time sending.
In this embodiment, by outputting the classification result corresponding to the target transaction data, it is able to achieve automatic implementation that the corresponding user terminal receives the information corresponding to the rule matching network output.
In one embodiment, a rule matching engine receives a rule configuration instruction sent by a rule configuration platform; and determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction. The rule matching engine acquires an initial rule matching network; matching the matching condition with each node in the initial rule matching network; when the node corresponding to the matching condition exists in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node, and the connection line between the nodes is determined based on the sequence of the matching condition; and determining a target rule matching network according to the nodes and the connection lines.
Acquiring initial transaction data and storing the initial transaction data to a message queue; the rule matching engine receives an initial transaction data subscription request and configures subscription information of initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
The rule matching engine acquires a target rule matching network and rule processing range information; generating a target matching network before acquiring the target rule matching network; screening the initial transaction data based on the rule processing range information to obtain target transaction data; matching the target transaction data with each node in the target rule matching network; determining an activated rule based on the successfully matched node and the connection line of the successfully matched node; and determining a classification result corresponding to the target transaction data based on the activated rule. And then, outputting a classification result corresponding to the target transaction data to a message platform, and feeding back the corresponding classification result to the user terminal by the message platform according to the classification result, wherein the feedback mode can be mail, short message, push notification and the like.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a transaction data processing device for realizing the transaction data processing method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation of one or more embodiments of the transaction data processing device provided below may refer to the limitation of the transaction data processing method hereinabove, and will not be repeated herein.
In one exemplary embodiment, as shown in FIG. 7, there is provided a transaction data processing apparatus comprising: a data acquisition module 701, a rule processing range acquisition module 702, a screening module 703, a matching module 704 and a result generation module 705, wherein:
a data acquisition module 701, configured to acquire initial transaction data;
a rule processing range obtaining module 702, configured to obtain a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
the screening module 703 is configured to screen the initial transaction data according to the community of the target user matched with the participation rule and the occurrence time of the initial transaction data, so as to obtain target transaction data;
a matching module 704, configured to match the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network;
the result generating module 705 is configured to obtain a classification result corresponding to the target transaction data based on the successfully matched node and the connection line of the successfully matched node.
In one exemplary embodiment, a transaction data processing apparatus further includes:
The receiving module is used for receiving the rule configuration instruction;
the sequence determining module is used for determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction;
the node connection determining module is used for determining connection lines among the nodes based on the sequence of the matching conditions by taking the matching conditions as nodes;
and the target rule matching network determining module is used for determining a target rule matching network according to the nodes and the connection lines.
In one exemplary embodiment, the node connection determination module includes:
an initial rule matching network obtaining unit, configured to obtain an initial rule matching network;
the matching unit is used for matching the matching condition with each node in the initial rule matching network;
and the shared node determining unit is used for taking the node successfully matched with the matching condition as a shared node when the node corresponding to the matching condition exists in the initial rule matching network.
In one exemplary embodiment, the result generation module 705 includes:
a rule activating unit, configured to determine an activated rule based on a node that is successfully matched and a connection line of the node that is successfully matched;
and the result determining unit is used for determining a classification result corresponding to the target transaction data based on the activated rule.
In one exemplary embodiment, the data acquisition module 701 includes:
the acquisition storage unit is used for acquiring initial transaction data and storing the initial transaction data into the message queue;
the initial transaction data acquisition unit is used for receiving an initial transaction data subscription request and configuring subscription information of the initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
In one exemplary embodiment, a transaction data processing apparatus further includes:
and the result output module is used for outputting a classification result corresponding to the target transaction data.
The various modules in the transaction data processing arrangement described above may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one exemplary embodiment, a computer device is provided, which may be a server, and the internal structure thereof may be as shown in fig. 8. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing transaction data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a transaction data processing method.
It will be appreciated by those skilled in the art that the structure shown in fig. 8 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one exemplary embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening the initial transaction data according to the group of the target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network;
And obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In one embodiment, the processor when executing the computer program further performs the steps of:
receiving a rule configuration instruction; determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction; taking each matching condition as a node, and determining a connecting line between the nodes based on the sequence of the matching conditions; and determining a target rule matching network according to the nodes and the connection lines.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring an initial rule matching network; matching the matching condition with each node in the initial rule matching network; and when the node corresponding to the matching condition exists in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node.
In one embodiment, the processor when executing the computer program further performs the steps of:
determining an activated rule based on the successfully matched node and the connection line of the successfully matched node; and determining a classification result corresponding to the target transaction data based on the activated rule.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring initial transaction data and storing the initial transaction data to a message queue; receiving an initial transaction data subscription request, and configuring subscription information of initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
In one embodiment, the processor when executing the computer program further performs the steps of:
and outputting a classification result corresponding to the target transaction data.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening the initial transaction data according to the group of the target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
Matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In one embodiment, the computer program when executed by the processor further performs the steps of:
receiving a rule configuration instruction; determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction; taking each matching condition as a node, and determining a connecting line between the nodes based on the sequence of the matching conditions; and determining a target rule matching network according to the nodes and the connection lines.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an initial rule matching network; matching the matching condition with each node in the initial rule matching network; and when the node corresponding to the matching condition exists in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node.
In one embodiment, the computer program when executed by the processor further performs the steps of:
Determining an activated rule based on the successfully matched node and the connection line of the successfully matched node; and determining a classification result corresponding to the target transaction data based on the activated rule.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring initial transaction data and storing the initial transaction data to a message queue; receiving an initial transaction data subscription request, and configuring subscription information of initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and outputting a classification result corresponding to the target transaction data.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
Screening the initial transaction data according to the group of the target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
In one embodiment, the computer program when executed by the processor further performs the steps of:
receiving a rule configuration instruction; determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction; taking each matching condition as a node, and determining a connecting line between the nodes based on the sequence of the matching conditions; and determining a target rule matching network according to the nodes and the connection lines.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an initial rule matching network; matching the matching condition with each node in the initial rule matching network; and when the node corresponding to the matching condition exists in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining an activated rule based on the successfully matched node and the connection line of the successfully matched node; and determining a classification result corresponding to the target transaction data based on the activated rule.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring initial transaction data and storing the initial transaction data to a message queue; receiving an initial transaction data subscription request, and configuring subscription information of initial transaction data based on the initial transaction data subscription request; when the initial transaction information exists in the message queue, acquiring the initial transaction data from the message queue based on subscription information of the initial transaction data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and outputting a classification result corresponding to the target transaction data.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A transaction data processing method, the method comprising:
acquiring initial transaction data;
acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
screening initial transaction data according to the group of target users matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
According to the sequence of each node in the target rule matching network, matching each node in the target transaction data target rule matching network;
and obtaining a classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
2. The method of claim 1, wherein prior to obtaining the target rule matching network and rule processing scope information, further comprising:
receiving a rule configuration instruction;
determining each matching condition corresponding to the rule and the sequence of the matching conditions based on the rule configuration instruction;
taking each matching condition as a node, and determining a connecting line between the nodes based on the sequence of the matching conditions;
and determining the target rule matching network according to the nodes and the connecting lines.
3. The method of claim 2, wherein said taking each of said matching conditions as a node comprises:
acquiring an initial rule matching network;
matching the matching condition with each node in the initial rule matching network;
and when the node corresponding to the matching condition exists in the initial rule matching network, the node successfully matched with the matching condition is used as a sharing node.
4. The method of claim 1, wherein the obtaining the classification result corresponding to the target transaction data based on the successfully matched node and the connection line of the successfully matched node comprises:
determining an activated rule based on the successfully matched node and the connection line of the successfully matched node;
and determining a classification result corresponding to the target transaction data based on the activated rule.
5. The method of claim 1, wherein the acquiring initial transaction data comprises:
acquiring initial transaction data and storing the initial transaction data into a message queue;
receiving an initial transaction data subscription request, and configuring subscription information of initial transaction data based on the initial transaction data subscription request; and when the initial transaction information exists in the message queue, acquiring initial transaction data from the message queue based on subscription information of the initial transaction data.
6. The method of claim 1, wherein after obtaining the classification result corresponding to the target transaction data based on the successfully matched node and the connection line of the successfully matched node, the method comprises:
And outputting a classification result corresponding to the target transaction data.
7. A transaction data processing device, the device comprising:
the data acquisition module is used for acquiring initial transaction data;
the rule processing range acquisition module is used for acquiring a target rule matching network and rule processing range information; wherein the rule processing range comprises the occurrence time of the initial transaction data and the belonging group of the target users participating in rule matching;
the screening module is used for screening the initial transaction data according to the community of the target user matched with the participation rule and the occurrence time of the initial transaction data to obtain target transaction data;
the matching module is used for matching the target transaction data with each node in the target rule matching network according to the sequence of each node in the target rule matching network;
and the result generation module is used for obtaining the classification result corresponding to the target transaction data based on the successfully matched nodes and the connection lines of the successfully matched nodes.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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| CN202311340075.XA CN117391856A (en) | 2023-10-16 | 2023-10-16 | Transaction data processing method, device, computer equipment and storage medium |
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