CN116915870B

CN116915870B - Task creation request processing method, device, electronic equipment and readable medium

Info

Publication number: CN116915870B
Application number: CN202311154439.5A
Authority: CN
Inventors: 孙艳青; 冯东; 郭振华; 王欣; 王战杰; 王亮亮
Original assignee: State Grid Information and Telecommunication Co Ltd; Beijing Guodiantong Network Technology Co Ltd
Current assignee: State Grid Information and Telecommunication Co Ltd; Beijing Guodiantong Network Technology Co Ltd
Priority date: 2023-09-08
Filing date: 2023-09-08
Publication date: 2023-11-24
Anticipated expiration: 2043-09-08
Also published as: CN116915870A

Abstract

The embodiment of the disclosure discloses a task creation request processing method, a device, electronic equipment and a readable medium. One embodiment of the method comprises the following steps: extracting target node information in response to detecting the task creation request; performing superior node query processing on the organization node information set to obtain a superior node information set; executing the creating step for each upper node information in the upper node information set: in response to determining that virtual task information exists in the set of virtual task information, performing the steps of: determining each piece of virtual task information as task information to be verified; performing state verification on each piece of task information to be verified to obtain each piece of target task information; generating detailed information of each task according to the information of each target task; adding each task detail information to a task detail information set; a set of task detail information is presented on a display device. The embodiment reduces the repeated transmission of the task information, thereby reducing the waste of network resources.

Description

Task creation request processing method, device, electronic equipment and readable medium

Technical Field

Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a task creation request processing method, apparatus, electronic device, and readable medium.

Background

With the wide popularization of the internet, online office has become a standardized office mode, and task issuing and creating in an internal network are common information technologies. Currently, the complete flow of task creation in an internal network is typically: generating task information comprising each index information and task description text by the client corresponding to the upper network node in the internal network, and then directly transmitting the task information to the client corresponding to each lower network node through the internal network; and after receiving the task information, the clients corresponding to the lower network nodes store the task information so as to complete task creation.

However, the inventors found that when task creation is performed in the above manner, there are often the following technical problems:

firstly, in the task issuing process, network congestion is caused by large issued task information, so that part of task information is lost due to packet loss in the transmission process, and accordingly, the missing task information needs to be issued again, and further network resources are wasted.

Secondly, in an actual service scenario, the repeatability of each index information issued to the client corresponding to the same node is high, and the repeated transmission causes waste of network resources.

Thirdly, when the client corresponding to the lower network node stores the task information, the storage space is wasted because the similarity among task description texts included in each received task information is higher and redundant text information in text content is more.

The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.

Disclosure of Invention

The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose a task creation request processing method, apparatus, electronic device, and computer readable medium to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a task creation request processing method, the method including: in response to detecting a task creation request sent by a target client, extracting target node information corresponding to the target client from the task creation request, wherein the task creation request comprises target node information, the target node information comprises target node identification information and father node identification information, the target node identification information is node identification information of a network node where the target client is located in an internal network, and the father node identification information included in the target node information is node identification information of a father level network node of the network node represented by the target node identification information; according to the target node information, performing superior node query processing on an organization node information set corresponding to the target node information to obtain each organization node information as a superior node information set; for each upper node information in the set of upper node information, the following creation step is performed: in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the set of virtual task information corresponding to the upper node information, performing the following steps: determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified; performing state verification on the determined task information to be verified to obtain target task information; generating detailed information of each task according to the target task information; adding each of the generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set; and displaying the updated task detail information set on the display equipment corresponding to the target client.

In a second aspect, some embodiments of the present disclosure provide a task creation request processing device, the device including: an extracting unit configured to extract, in response to detection of a task creation request issued by a target client, target node information corresponding to the target client from the task creation request, where the task creation request includes target node information including target node identification information and parent node identification information, the target node identification information being node identification information of a network node in which the target client is located in an internal network, and the parent node identification information included in the target node information being node identification information of a parent network node of a network node represented by the target node identification information; the processing unit is configured to perform superior node query processing on the organization node information set corresponding to the target node information according to the target node information to obtain each organization node information as a superior node information set; an execution unit configured to execute, for each of the upper node information in the upper node information set, the following creation step: in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the set of virtual task information corresponding to the upper node information, performing the following steps: determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified; performing state verification on the determined task information to be verified to obtain target task information; generating detailed information of each task according to the target task information; adding each of the generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set; and displaying the updated task detail information set on the display equipment corresponding to the target client.

In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors causes the one or more processors to implement the method described in any of the implementations of the first aspect above.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

The above embodiments of the present disclosure have the following advantageous effects: the task creation request processing method of some embodiments of the present disclosure can reduce repeated transmission of task information, thereby reducing waste of network resources. Specifically, the reason for wasting network resources is that: in the task issuing process, because the issued task information is large in quantity, network congestion is caused, and part of task information is lost due to packet loss in the transmission process, so that the missing task information needs to be issued again, and further network resource waste is caused. Based on this, the task creation request processing method of some embodiments of the present disclosure first extracts, in response to detection of a task creation request issued by a target client, target node information corresponding to the target client from the task creation request. The task creation request includes target node information, where the target node information includes target node identification information and parent node identification information, the target node identification information is node identification information of a network node where the target client is located in an internal network, and the parent node identification information included in the target node information is node identification information of a parent network node of the network node represented by the target node identification information. Thus, target node information characterizing a corresponding network node of the target client in the internal network may be extracted from the task creation request. And then, according to the target node information, carrying out superior node query processing on the organization node information set corresponding to the target node information to obtain each organization node information as a superior node information set. Thus, the upper node information can be obtained. The respective upper node information may characterize respective upper network nodes in the internal network corresponding to the target client. Then, for each upper node information in the upper node information set described above, the following creation step is performed: in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the set of virtual task information corresponding to the upper node information, performing the following steps: and determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified. Therefore, whether the virtual task information issued to the target client exists or not can be determined in the virtual task information set corresponding to the upper node information, and the virtual task information issued to the target client is determined to be the task information to be verified. And carrying out state verification on the determined task information to be verified to obtain target task information. Thus, each of the task information to be verified that passes the verification can be determined as each of the target task information for generating each of the task detail information. And generating detailed information of each task according to the target task information. Thus, the respective task detail information can be generated. And adding each generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set. Thus, each newly generated task detail information can be added to the task detail information set. And displaying the updated task detail information set on the display equipment corresponding to the target client. Thus, the generated task detail information can be presented to complete task creation. The method adopts a mode of actively acquiring each piece of virtual task information corresponding to the target node information from the virtual task information set corresponding to the upper node information, and the amount of task information which is acquired at a time is small because the time for a client corresponding to each lower network node to initiate a task creation request in an internal network is different, so that the amount of task information which is issued by the client corresponding to the upper network node can be reduced. Therefore, through the mode, the occurrence frequency of network congestion caused by larger downlink information quantity can be reduced, so that information loss caused by network congestion packet loss in the task information transmission process can be reduced, and further repeated transmission of task information and waste of network resources can be reduced.

Drawings

The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.

FIG. 1 is a flow chart of some embodiments of a task creation request processing method according to the present disclosure;

FIG. 2 is a schematic diagram of the architecture of some embodiments of a task creation request processing device according to the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

FIG. 1 illustrates a flow 100 of some embodiments of a task creation request processing method according to the present disclosure. The task creation request processing method comprises the following steps:

In step 101, in response to detecting a task creation request sent by a target client, target node information corresponding to the target client is extracted from the task creation request.

In some embodiments, an executing body (e.g., a computing device) of the task creation request processing method may extract target node information corresponding to a target client from the task creation request in response to detecting the task creation request issued by the target client. The execution body may receive the task creation request sent by the target client through a wired connection manner or a wireless connection manner. Wherein the task creation request may include target node information. The task creation request may be an interface call request issued when the target client user calls a task creation interface. The target node information may include target node identification information and parent node identification information. The target node identification information may be node identification information of a network node in which the target client is located in the internal network. The parent node identification information included in the target node information may be node identification information of a parent network node of the network node represented by the target node identification information. The internal network may be an enterprise intranet employing a tree network topology. The target client may be a client corresponding to the execution subject. In practice, the execution body may extract the target node information from the task creation by extracting JSON attribute.

It should be noted that the wireless connection may include, but is not limited to, 3G/4G connections, wiFi connections, bluetooth connections, wiMAX connections, zigbee connections, UWB (ultra wideband) connections, and other now known or later developed wireless connection means.

The computing device may be hardware or software. When the computing device is hardware, the computing device may be implemented as a distributed cluster formed by a plurality of servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices listed above. It may be implemented as a plurality of software or software modules, for example, for providing distributed services, or as a single software or software module. The present invention is not particularly limited herein. It should be appreciated that there may be any number of computing devices as desired for an implementation.

Step 102, according to the target node information, performing superior node query processing on the organization node information set corresponding to the target node information, and obtaining each organization node information as the superior node information set.

In some embodiments, the executing body may perform, according to the target node information, a superior node query process on an organization node information set corresponding to the target node information, to obtain each organization node information as a superior node information set. Wherein each organization node information in the organization node information set corresponding to the target node information may represent each distinct network node in the internal network. The organization node information set may be a data table in a database corresponding to the target client. The different network nodes may be different network nodes in the internal network from the network node represented by the target node identification information. The organization node information in the organization node information set may include organization node identification information and organization parent node identification information. The organization node identification information may be node identification information of a corresponding distinct network node. The organization parent node identification information may be node identification information of a parent level network node of the network node characterized by the organization node identification information. In practice, when the network node represented by the organization node identification information included in the organization node information does not have a corresponding parent level network node in the internal network, the organization node information does not include the organization parent node identification information. The upper node information set may be an information set representing each upper network node corresponding to the network node where the target client is located in the internal network. For example, the network node where the target client is located may be C1. In the internal network, the parent level network node corresponding to the network node C1 may be B1. The parent network node corresponding to network node B1 may be A1. The upper network node corresponding to the above network node C1 may include B1 and A1.

In some optional implementations of some embodiments, the executing body may perform a superior node query process on an organization node information set corresponding to the target node information according to the target node information to obtain each organization node information as a superior node information set by:

first, parent node identification information included in the target node information is determined as target parent node identification information.

Second, based on the target father node identification information, the following node inquiry steps are executed:

a first sub-step of selecting organization node information satisfying parent node conditions from the above-mentioned organization node information set according to the target parent node identification information. The parent node condition may be that the target parent node identification information is the same as the organization parent node identification information included in the organization node information.

And a second sub-step of, in response to determining that the determined organization node information includes organization parent node identification information, determining the organization parent node identification information included in the determined organization node information as target parent node identification information and performing the above-described node query step again.

And thirdly, determining the selected organization node information as a superior node information set. Thus, the above steps can be used to query the organization node information set corresponding to the above target node information for the organization node information characterizing each upper network node corresponding to the network node characterized by the above target node identification information.

Step 103, for each upper node information in the upper node information set, performing the following creation steps:

step 1031, in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the set of virtual task information corresponding to the upper node information, performing the steps of:

step 10311, determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified.

In some embodiments, the executing body may determine each of the at least one virtual task information as the task information to be verified. The virtual task information in the virtual task information set may be task information that is logically issued. The virtual task information corresponds to a task issuing state. The task issuing status may be a text label. The logical issuing may indicate that the corresponding virtual task information is not actually transmitted to the client corresponding to the network node, which is indicated by the issuing node identification information in the virtual task information, but the corresponding task issuing state is updated to "issued". When the task issuing status is "issued", the corresponding virtual task information that can be actually characterized can be acquired by the execution subject. The virtual task information in the virtual task information set may include task identification information, issuing node identification information, initiating node identification information, index set identification information, task creation time, task deadline, and task description text information. The node identification information of the network node to which the corresponding virtual task information is to be transmitted may be the node identification information of the network node. The initiating node identification information may be node identification information of a network node where the client terminal that generates the corresponding virtual task information is located. The task identification information may be a character string for identifying corresponding virtual task information. The index set identification information may be composed of index identification information included in each index information and a preset splice. The index identification information may be a character string for identifying the corresponding index information. The index information may include, but is not limited to, primary index information, secondary index information, and tertiary index information. The first-level index information may include first-level index identification information and a first-level index name. The secondary index information may include secondary index identification information and a secondary index name. The three-level index information may include three-level index identification information, three-level index type information, three-level index name, and three-level index result information. In practice, the first-level index represented by the index information (first-level index information) whose index type is "first-level index" may be a comprehensive index. The secondary index represented by the index information (secondary index information) whose index type is the "secondary index" may be an index obtained by refining the integrated index represented by the above-mentioned primary index information. The three-level index represented by the index information (three-level index information) whose index type is the "three-level index" may be an index which is more specific and which requires data statistics under the two-level index represented by the above-described two-level index information. For example, the primary index represented by the primary index information may be "basic level organization construction", the secondary index represented by the secondary index information may be "organization scale construction", and the tertiary index represented by the tertiary index information may be "the number of organizations of 51-100 persons in scale". And each index type corresponds to each index information corresponding to each index identification information constituting the index set identification information. The index type may be a text label, which is used to characterize the type of the corresponding index information. The index types may include, but are not limited to, "primary index", "secondary index", and "tertiary index". For example, the preset splice may include "-" and "|". The index type of the index information corresponding to the index identification information of "FW001" is a possible "first-order index". The index type of the index information corresponding to the index identification information "DZ001" may be "secondary index". The index type of the two index information whose index identification information is "KZ001" and "KZ009" respectively may be both "three-level index". The index set identification information composed may be "FW001-DZ001-KZ001|kz002". The task description text information may be text information for making supplementary explanation and description of the corresponding virtual task information. In practice, first, the execution body may determine node identification information included in the upper node information as access node identification information. Then, the client corresponding to the network node characterized by the access node identification information can be accessed. Then, whether the issuing node identification information included in each piece of virtual task information is the same as the target node identification information included in the target node information or not can be determined in the virtual task information set corresponding to the accessed client. Finally, each piece of virtual task information with the same issuing node identification information as the upper target node identification information can be determined to be each piece of virtual task information corresponding to the target node information, and each piece of virtual task information corresponding to the target node information can be obtained through remote procedure call.

And step 10312, performing state verification on the determined task information to be verified to obtain target task information.

In some embodiments, the executing body may perform state verification on the determined task information to be verified to obtain each target task information.

In some optional implementations of some embodiments, the executing body may perform state verification on the determined task information to be verified to obtain the target task information by:

the first step, for each piece of task information to be verified in the above pieces of task information to be verified, the following verification steps are executed:

and a first sub-step of determining the task information to be verified as invalid task information in response to determining that the task issuing state corresponding to the task information to be verified does not meet the task state condition. The task status condition may be that a task issue status corresponding to the task information to be verified is "issued".

And a second sub-step of determining the task information to be verified as invalid task information in response to determining that the task information to be verified does not meet the task time condition. The task time condition may be that the time when the execution body verifies the task information to be verified does not exceed the task deadline included in the task information to be verified. For example, the time when the executing body verifies the task information to be verified may be "2023-08-12-14:23", the task deadline included in the task information to be verified may be "2023-08-31-23:59", and the executing body may determine that the task information to be verified satisfies the task time condition. Or the time when the executing body verifies the task information to be verified may be "2023-09-01-14:23", the task deadline included in the task information to be verified may be "2023-08-31-23:59", and then the executing body may determine that the task information to be verified does not meet the task time condition.

And a third sub-step of determining the task information to be verified as target task information in response to determining that the task issuing state corresponding to the task information to be verified meets the task state condition and the task information to be verified meets the task time condition. The target task information may be task information to be verified for generating respective task detail information. Thus, each task information to be verified can be verified to determine the target task information.

Step 10313, generating each task detail information according to each target task information.

In some embodiments, the execution body may generate each task detail information according to each target task information.

In some optional implementations of some embodiments, the executing entity may generate each task detail information according to each target task information by:

the first step, for each target task information in the target task information, performs the following steps:

a first sub-step of determining the target task information as invalid task information in response to determining that task detail information corresponding to the target task information exists in a task detail information set corresponding to the target node information. In practice, first, the execution subject may determine, in the task detail information set, whether the task identification information included in each task detail information is the same as the task identification information included in the target task information. Then, task detail information, which is the same as task identification information included in the target task information, as task detail information corresponding to the target task information, may be determined as task identification information included in the task detail information set.

And a second sub-step of generating each task index information according to the index set identification information included in the target task information.

And a third sub-step of determining task detail information including task identification information, issuing node identification information, initiating node identification information, task creation time, task deadline and task description text information included in the task index information and the target task information. Thus, task detail information can be generated from the target task information through the above steps.

In some optional implementations of some embodiments, the executing entity may generate each task index information according to index set identification information included in the target task information by:

the first step, the index set identification information included in the target task information is input to an input layer in a preset index information generation model, and an identification verification result is obtained. The index information generation model comprises an input layer, a preprocessing layer, a primary index classification model, a secondary index classification model, a tertiary index classification model and an output layer. The preset index information generating model may be a classification model with index set identification information as input and each task index information as output. The input layer of the index information generation model may verify the input index set identification information (for example, regular rule verification) to determine whether the index set identification information generates information loss or transmission error in the transmission process. The identification verification result can represent a verification result obtained after the input index set identification information is verified. In practice, the above-mentioned identification verification result may be a boolean type variable. For example, when the variable value of the identification verification result is "TRUE", it may be characterized that the input index set identification information is normal, that is, no information loss or transmission error occurs during the transmission process. When the variable value of the identification verification result is 'FALSE', the input index set identification information is characterized as abnormal, namely, the index set identification information generates information missing or transmission error in the transmission process.

And secondly, in response to determining that the identification verification result represents that the index set identification information is normal, inputting the index set identification information into the preprocessing layer to obtain the index identification information. Wherein the index identification information comprises primary index identification information, secondary index identification information and three-level index identification information. The preprocessing layer may be configured to divide the index set identifier information to obtain index identifier information. In practice, the preprocessing layer may divide the index set identification information by respective preset splice symbols constituting the index set identification information. For example, the index set identification information may be "FW001-DZ001-KZ001|KZ002|KZ009". The first-level index identification information included in the index identification information obtained after the division of the pretreatment layer may be "FW001", the second-level index identification information may be "DZ001", and the three index identification information may be "KZ001", "KZ002", and "KZ009", respectively.

And thirdly, inputting the first-level index identification information into the first-level index classification model to obtain first-level index classification information. The first-level index classification information comprises a first-level classification result, a first-level index name and second-level index information. The first-level index classification model may be a classification model in which first-level index identification information is input and first-level index classification information is output. The primary index classification model may sequentially compare the input primary index identification information with primary index identification information included in each preset primary index information in a preset primary index table. The preset primary index table may be established based on the primary index information received by the target client. The preset primary index information may be primary index information received by the target client. The primary classification result can represent whether the input primary index identification information is successfully classified. In practice, the above-mentioned primary classification result may be a boolean type variable. For example, when the variable value of the primary classification result is "TRUE", it may be characterized that the input primary index identification information is successfully classified, that is, the primary index identification information included in the preset primary index table is the same as the preset primary index identification information. When the variable value of the primary classification result is "FALSE", it may be characterized that the classification of the input primary index identification information fails, that is, the preset primary index table does not have the primary index identification information which is the same as the input primary index identification information. When the variable value of the primary index classification result is 'FALSE', the primary index name and the secondary index information included in the primary index classification information output by the primary index classification model are null values. The primary index name may be an index name corresponding to the input primary index identification information. For example, the input primary index identification information may be "FW001", and the corresponding primary index name may be "infrastructure construction". The secondary index information may be index information for determining a preset secondary index table corresponding to the input primary index identification information among the respective preset secondary index tables. One preset primary index information in the preset primary index table corresponding to each secondary index table in the preset secondary index tables. Each of the predetermined secondary index tables may be established based on respective secondary index information received by the target client and corresponding to the one predetermined primary index information.

And fourthly, responding to the determination that the primary classification result represents the classification failure, and sending a task index request to a client corresponding to the initiating node identification information included in the target task information so as to acquire each task index information. Wherein the task index request includes the index identification information.

And fifthly, in response to determining that the primary classification result represents successful classification, the secondary index information and the secondary index identification information are input into the secondary index classification model to obtain secondary index classification information. The secondary index classification information comprises a secondary classification result, a secondary index name and tertiary index information. The secondary index classification model may be a classification model in which secondary index identification information and secondary index information are input and secondary index classification information is output. The secondary index classification model can sequentially compare the input secondary index identification information with each preset secondary index information in the preset secondary index table corresponding to the input secondary index information. The preset secondary index information may be secondary index information received by the target client and corresponding to the one preset primary index information. The secondary classification result may represent whether the input secondary index identification information is classified successfully. In practice, the secondary classification result may be a boolean type variable. For example, when the variable value of the secondary classification result is "TRUE", it may be characterized that the classification of the input secondary index identification information is successful, that is, the preset secondary index table corresponding to the input secondary index information has preset secondary index information including the same secondary index identification information as the input secondary index identification information. When the variable value of the secondary classification result is "FALSE", it may be characterized that the classification of the input secondary index identification information fails, that is, the preset secondary index table corresponding to the input secondary index information does not have the preset secondary index information including the secondary index identification information identical to the input secondary index identification information. When the variable value of the secondary index classification result is 'FALSE', the secondary index classification information output by the secondary index classification model comprises a secondary index name and secondary index information which are null values. The secondary index name may be an index name corresponding to the input secondary index identification information. For example, the input secondary index identification information may be "DZ001", and the corresponding secondary index name may be "organization trade choice". The three-level index information may be index information for determining a preset three-level index table corresponding to the input two-level index identification information among the respective preset three-level index tables. Each preset three-level index table in the preset three-level index tables corresponds to one preset two-level index information in the preset two-level index tables corresponding to the two-level index information. Each of the predetermined three-level index tables may be established based on the respective three-level index information received by the target client corresponding to the one predetermined two-level index identification information. The received three-level index information may include three-level index identification information, three-level index type information, three-level index name, and three-level index result information.

And sixthly, responding to the determination that the secondary classification result represents the classification failure, and sending the task index request to the client corresponding to the initiating node identification information included in the target task information so as to acquire each task index information.

Seventh, in response to determining that the secondary classification result characterizes the classification success, for each of the respective tertiary index identification information, performing the following steps:

and a first sub-step of inputting the three-level index information and the three-level index identification information into the three-level index classification model to obtain three-level index classification information. The three-level index classification information comprises three-level classification results, three-level index type information, three-level index names and three-level index result information. The three-level index classification model may be a classification model in which three-level index identification information and three-level index information are input and three-level index classification information is output. The three-level index classification model can sequentially compare the input three-level index identification information with each preset three-level index information in the preset three-level index table corresponding to the input three-level index information. The preset tertiary index information may be tertiary index information received by the target client and corresponding to the one preset secondary index information. The three-level classification result can represent whether the input three-level index identification information is successfully classified or not. In practice, the three-level classification result may be a boolean type variable. For example, when the variable value of the three-level classification result is "TRUE", it may be characterized that the input three-level index identification information is successfully classified, that is, the preset three-level index table corresponding to the input three-level index information includes three-level index identification information identical to the input three-level index identification information. When the variable value of the three-level classification result is "FALSE", it may be characterized that the input three-level index identification information fails to be classified, that is, the preset three-level index table corresponding to the input three-level index information does not have preset three-level index information, where the three-level index identification information is the same as the input three-level index identification information. When the variable value of the three-level classification result is 'FALSE', the three-level index classification information output by the three-level index classification model comprises three-level index type information, three-level index names and three-level index result information which are all null values. The three-level index name may be a name corresponding to the input three-level index identification information. For example, the input three-level index identification information may be "KZ001", and the corresponding three-level index name may be "the number of tissues of 100 or more". The three-level index type information can be a text label for representing the corresponding three-level index result information type. The three level indicator types described above may include "system statistics" and "manual recording. For example, the three-level index name may be "the number of tissues of 100 persons or more", the three-level index result information may be "97", and the three-level index type information corresponding to the three-level index result information may be "system statistics".

And a second sub-step of determining the three-level index identification information as target three-level index identification information in response to determining that the three-level classification result characterizes the classification failure. The target three-level index identification information may be three-level index identification information used for sending a target index request to a client corresponding to the network node represented by the initiating node identification information in the target task information.

And a third sub-step of inputting the index item identification information, the primary index classification information, the secondary index classification information and the tertiary index classification information to the output layer to obtain task index information in response to determining that the three-stage classification result represents successful classification. In practice, the output layer may determine the primary index identification information, the secondary index identification information, the tertiary index identification information, and primary index names in the primary index classification information, secondary index names in the secondary index classification information, tertiary index type information, tertiary index names, and tertiary index result information included in the tertiary index classification information as task index information. For example, the task index information may be "{ primary index identifier: "FW001", first order index name: "basic layer organization construction", secondary index identification: "DZ001", second level index name: "tissue replacement election", three-level index identification: "KZ001", three-level index name: "tissue number of 100 people above", three-level index results: 97, three-level index type: "System statistics" }.

Eighth, in response to determining that at least one target tertiary index identification information exists, a target index request is sent to a client corresponding to the initiating node identification information included in the target task information to acquire each task index information. Wherein the target index request includes the primary index identification information, the secondary index identification information, and the determined at least one target tertiary index identification information.

The first to eighth steps are taken as an invention point of the embodiments of the present disclosure, and solve the second technical problem mentioned in the background art, that in an actual service scenario, the repeatability of each index information issued to the client corresponding to the same node is often higher, and the repeated transmission leads to the waste of network resources. Factors that lead to network resource waste are often as follows: in an actual service scene, the repeatability of each index information issued to the client corresponding to the same node is high, and the repeated transmission causes the waste of network resources. If the above factors are solved, the effect of reducing network resource waste can be achieved. To achieve this effect, the present disclosure introduces an index information generation model. Firstly, inputting index set identification information included in the target task information into an input layer in a preset index information generation model to obtain an identification verification result. The index information generation model comprises an input layer, a preprocessing layer, a primary index classification model, a secondary index classification model, a tertiary index classification model and an output layer. Thus, it is possible to determine whether or not the index set identification information has information missing or transmission error. And then, in response to determining that the identification verification result represents that the index set identification information is normal, inputting the index set identification information into the preprocessing layer to obtain the index identification information. Wherein the index identification information comprises primary index identification information, secondary index identification information and three-level index identification information. Thereby, index identification information for generating task index information can be obtained. And then, inputting the first-level index identification information into the first-level index classification model to obtain first-level index classification information. The first-level index classification information comprises a first-level classification result, a first-level index name and second-level index information. Thus, whether the target client receives the first-level index information corresponding to the first-level index identification information can be determined by the first-level index classification model. And then, in response to determining that the primary classification result represents the classification failure, sending a task index request to a client corresponding to the initiating node identification information included in the target task information to acquire each task index information, wherein the task index request comprises the index identification information. Thus, when it is determined that the target client does not receive the first-level index information corresponding to the first-level index identification information, a request may be sent to the client corresponding to the network node represented by the initiating node identification information to obtain each task index information corresponding to the index identification information. And secondly, in response to determining that the primary classification result represents successful classification, the secondary index information and the secondary index identification information are input into a secondary index classification model to obtain secondary index classification information. The secondary index classification information comprises a secondary classification result, a secondary index name and tertiary index information. Thus, when it is determined that the target client has received the primary index information corresponding to the primary index identification information, it may be determined whether the target client has received the secondary index information corresponding to the secondary index identification information through the secondary index classification model. And then, in response to determining that the secondary classification result represents the classification failure, sending the task index request to the client corresponding to the initiating node identification information included in the target task information so as to acquire each task index information. Thus, when it is determined that the target client does not receive the secondary index information corresponding to the secondary index identification information, a request may be sent to a client corresponding to the network node represented by the originating node identification information to obtain each task index information corresponding to the index identification information. Then, in response to determining that the secondary classification result characterizes the classification as successful, for each of the respective tertiary index identification information, performing the following steps: and inputting the three-level index information and the three-level index identification information into the three-level index classification model to obtain three-level index classification information. The three-level index classification information comprises three-level classification results, three-level index type information, three-level index names and three-level index result information. Thus, when it is determined that the target client has received the secondary index information corresponding to the secondary index identification information, it may be determined whether the target client has received the tertiary index information corresponding to the tertiary index identification information through the tertiary index classification model. And determining the three-level index identification information as target three-level index identification information in response to determining that the three-level classification result represents the classification failure. And in response to determining that the three-level classification result represents successful classification, inputting the index item identification information, the first-level index classification information, the second-level index classification information and the third-level index classification information into the output layer to obtain task index information. Thus, the first-level index classification model, the second-level index classification model and the third-level index classification model can determine that the target client side has received the first-level index information corresponding to the first-level index identification information, the second-level index information corresponding to the second-level index identification information and the third-level index information corresponding to the third-level index identification information, and the received first-level index information, second-level index information and third-level index information can be directly multiplexed to form task index information. And in response to determining that at least one target three-level index identification information exists, sending a target index request to a client corresponding to the initiating node identification information included in the target task information so as to acquire each task index information. Wherein the target index request includes the primary index identification information, the secondary index identification information, and the determined at least one target tertiary index identification information. Thus, when it is determined that the target client does not receive the three-level index information corresponding to the three-level index identification information of each target, a target index request may be sent to the client corresponding to the initiating node identification information included in the target task information to obtain the task index information. Therefore, by adopting the mode of generating the model by the index set identification information and the index information, the task index information request is initiated to the client corresponding to the network node represented by the initiation node identification information only when the target client does not receive the same index information, so as to acquire the task index information, thereby reducing the number of repeated index information sent to the target client by the client corresponding to the superior network node, reducing the repeated transmission of the index information, and further reducing the network resource waste.

Step 10314, adding the generated respective task detail information to the task detail information set corresponding to the target node information to update the task detail information set.

In some embodiments, the execution body may add the generated respective task detail information to a task detail information set corresponding to the target node information to update the task detail information set.

And step 10315, displaying the updated task detail information set on the display device corresponding to the target client.

In some embodiments, the executing entity may display the updated task detail information set on a display device corresponding to the target client.

Optionally, the creating step may further include the steps of:

in response to detecting an information storage request from the target client, extracting storage condition information from the information storage request and performing the steps of:

and a first sub-step of determining each task detail information meeting the information storage condition corresponding to the storage condition information in the updated task detail information set as a target task detail information set. The information storage request may be an interface call request issued when the target client user calls an information storage request interface. The storage condition information may be information for filtering task detail information input by the target client user. For example, the above storage condition information may be "task expiration date: 2023-08-31". The information storage condition corresponding to the above-described storage condition information may be that the task detail information includes a task expiration date of "2023-08-31".

And a second sub-step of determining task description text information included in each target task detail information in the target task detail information set as a task description text information set.

A third sub-step of executing the following steps for each two pieces of task description text information in the task description text set:

and step one, inputting the text information of the two task descriptions into a preset text semantic similarity model to obtain the text semantic similarity. The preset text semantic similarity model can be used for determining the text semantic similarity between two task description text messages. The preset text semantic similarity model can be a natural language processing model or a neural network model which takes two task description text information as input and takes text semantic similarity as output. For example, the text semantic similarity model may be a BERT model or a recurrent neural network model.

And secondly, in response to determining that the text semantic similarity is greater than or equal to a preset similarity threshold, inputting the first task description text information into a preset text keyword extraction model to obtain each task description text keyword as a task description text keyword set. The first task description text is task description text information in the two task description text information, and the number of characters of the first task description text is larger than that of the other task description text information in the two task description text information. The preset text keyword extraction model may be used to extract text keywords of the first task description text. The preset text keyword extraction model may be a natural language processing model or a neural network model, which takes text information as input and text keywords as output. For example, the preset text keyword extraction model may be a Sequence-to-Sequence model or a TextRank model.

And a third sub-step of replacing task description text information in target task detail information corresponding to the first task description text information in the target task detail information set with the task description text keyword set so as to update the target task detail information set.

And a second step of storing the updated target task detail information set to a target database. The target database may be a database corresponding to the target client.

The above related content is used as an invention point of the embodiments of the present disclosure, which solves the technical problem mentioned in the background art, namely, when a client corresponding to a third "lower network node" stores task information, the storage space is wasted because the similarity between task description texts included in each received task information is higher and redundant text information in text content is more. Factors that lead to waste of storage resources are often as follows: when the client corresponding to the lower network node stores task information, the similarity among task description texts included in each received task information is higher, and redundant text information in text content is more, so that the waste of storage space is caused. If the above factors are solved, the effect of reducing the waste of storage resources can be achieved. To achieve this, the present disclosure introduces a text semantic similarity model and a text keyword extraction model. First, in response to detecting an information storage request issued by the target client, storage condition information is extracted from the information storage request and the following steps are performed: and determining each task detail information meeting the information storage condition corresponding to the storage condition information in the updated task detail information set as a target task detail information set. Thus, the target task detail information set which needs to be stored by the target client user can be obtained. And determining task description text information included in each target task detail information in the target task detail information set as a task description text information set. For each two task description text messages in the task description text set, executing the following steps: and inputting the text information of the two task descriptions into a preset text semantic similarity model to obtain the text semantic similarity. Therefore, the text semantic similarity between the two task description text messages can be obtained to judge whether the two task description text messages are redundant text messages or not. And in response to determining that the text semantic similarity is greater than or equal to a preset similarity threshold, inputting the first task description text information into a preset text keyword extraction model to obtain each task description text keyword as a task description text keyword set. The first task description text is task description text information in the two task description text information, and the number of characters of the first task description text is larger than that of the other task description text information in the two task description text information. Therefore, when the text semantic similarity is greater than or equal to a preset similarity threshold, the first task description text information can be determined to be redundant text information, and text keywords can be extracted from the first task description text information. And replacing task description text information in target task detail information corresponding to the first task description text information in the target task detail information set with the task description text keyword set so as to update the target task detail information set. Therefore, the waste of the redundant text information to the storage space can be reduced by replacing the first task description text with the task description text keywords. The updated set of objective task detail information is stored to the objective database. Therefore, the text information with higher similarity can be replaced and stored in the form of text keywords through the text semantic similarity model and the text keyword extraction model, so that the storage of redundant information is reduced, and the waste of storage space is reduced.

Optionally, the method may further include the steps of:

the first step, in response to detecting a task release request sent by the target client, target node information corresponding to the target client is obtained.

Second, in response to determining that the obtained target node information satisfies the publishing node condition, performing the task publishing step of:

and a first sub-step of extracting issuing task information, issuing task index information and task state information from the task issuing request. The task issuing information may include task identification information, task creation time, and issuing node identification information. The task issuing information and the task issuing index information may be information for generating virtual task information, which is input by the target client user. The downlink index information may include primary index information, secondary index information, and respective tertiary index information. The task state information may be information for adjusting a task issuing state corresponding to the generated virtual task information. The task state information may be a text label. The publishing node condition may be that a lower network node corresponding to a network node represented by the target node identification information in the target node information exists in the internal network. In practice, first, the execution body may determine whether or not there is organization node information including parent node identification information identical to target node identification information included in the target node information, from among an organization node information set corresponding to the target node information. Then, in response to determining that organization node information having parent node identification information included in a set of organization node information corresponding to the target node information is the same as target node identification information included in the target node information, the execution subject may determine that the target node information satisfies the distribution node condition.

And a second sub-step of generating the issuing task deadline according to the issuing task information and the preset task period. In practice, the execution body may add the task creation time and the preset task period included in the issuing task information to generate the issuing task deadline.

And a third sub-step of generating the identification information of the downlink index set according to the downlink index information. In practice, the execution body may connect the primary index identification information, the secondary index identification information, each tertiary index identification information and the preset splice symbol included in the downlink index information, so as to generate downlink index set identification information.

And a fourth sub-step of generating task description text information according to the issuing task information, the issuing index information and the issuing task deadline. In practice, first, the execution body may determine, as each keyword, a task creation time in the issuing task information, each index information included in the issuing index information, and the issuing task deadline. Then, the number of three-level index type information, which is "system statistics", among the respective three-level index type information included in the issued index information may be determined as the first index number. Then, the number of three-level index type information, which is "manual recording" among the three-level index type information included in the issue index information, may be determined as the second index number. Finally, the keywords, the first index number and the second index number may be embedded into a preset description text to generate task description text information. For example, the preset description text may be "one, task completion time: task creation time two, issue task deadline, index filling requirement: 1. the quantitative planning task is required to complete the filling work of [ primary index name ], [ secondary index name ], [ each tertiary index name ]. 2. The task system automatically obtains the items of the index (the first index number) and manually reports the items of the index (the second index number). 3. Preset content: each unit is required to carefully and timely finish the quantitative plan index filling work according to the detailed requirements of each index. The process is described.

And a fifth sub-step of determining virtual task information according to the issuing task information, the task description text information, the issuing index set identification information, the target node information and the issuing task deadline. In practice, first, the executing entity may determine the target node identification information as the originating node identification information. The above-described issuing task deadline may then be determined as a task deadline. The above-described issued index set identification information may then be determined as index set identification information. Finally, task identification information, task creation time, issuing node identification information, the initiating node identification information, the task deadline, the index set identification information and the task description text information included in the task issuing information can be determined to be virtual task information.

And a sixth sub-step of adding the determined virtual task information to a virtual task information set corresponding to the target node information, for generating task detail information for each client corresponding to each organization node information satisfying the lower node condition in the organization node information set. The lower node condition may be that organization parent node identification information included in the organization node information set is the same as target node identification information included in the target node information.

And a seventh sub-step of updating the task issuing state corresponding to the generated virtual task information according to the task state information. In practice, the execution subject may update the task issuing state corresponding to the generated virtual task information through the text information characterized by the task state information. For example, the task status information may be "issued", and the execution subject may update the task issue status corresponding to the generated virtual task information to "issued". Therefore, the target client can realize the logic issuing of the virtual task information through the steps.

With further reference to fig. 2, as an implementation of the method shown in the figures, the present disclosure provides some embodiments of a task creation request processing device, which correspond to those method embodiments shown in fig. 1, and which are particularly applicable in various electronic apparatuses.

As shown in fig. 2, the task creation request processing device 200 of some embodiments includes: an extraction unit 201, a processing unit 202, and an execution unit 203. Wherein the extracting unit 201 is configured to extract, in response to detecting a task creation request sent by a target client, target node information corresponding to the target client from the task creation request, where the task creation request includes target node information, the target node information includes target node identification information and parent node identification information, the target node identification information is node identification information of a network node where the target client is located in an internal network, and the parent node identification information included in the target node information is node identification information of a parent network node of the network node characterized by the target node identification information; the processing unit 202 is configured to perform a superior node query process on an organization node information set corresponding to the target node information according to the target node information, so as to obtain each organization node information as a superior node information set; the execution unit 203 is configured to execute the following creation steps for each of the above-described upper node information sets: in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the set of virtual task information corresponding to the upper node information, performing the following steps: determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified; performing state verification on the determined task information to be verified to obtain target task information; generating detailed information of each task according to the target task information; adding each of the generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set; and displaying the updated task detail information set on the display equipment corresponding to the target client.

It will be appreciated that the elements described in the apparatus 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and resulting benefits described above for the method are equally applicable to the apparatus 200 and the units contained therein, and are not described in detail herein.

Referring now to fig. 3, a schematic diagram of an electronic device 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The computer program, when executed by the processing means 301, performs the functions defined in the methods of some embodiments of the present disclosure.

It should be noted that, the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be embodied in an electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: in response to detecting a task creation request sent by a target client, extracting target node information corresponding to the target client from the task creation request, wherein the task creation request comprises target node information, the target node information comprises target node identification information and father node identification information, the target node identification information is node identification information of a network node where the target client is located in an internal network, and the father node identification information included in the target node information is node identification information of a father level network node of the network node represented by the target node identification information; according to the target node information, performing superior node query processing on an organization node information set corresponding to the target node information to obtain each organization node information as a superior node information set; for each upper node information in the set of upper node information, the following creation step is performed: in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the set of virtual task information corresponding to the upper node information, performing the following steps: determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified; performing state verification on the determined task information to be verified to obtain target task information; generating detailed information of each task according to the target task information; adding each of the generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set; and displaying the updated task detail information set on the display equipment corresponding to the target client.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes an extraction unit, a processing unit, and an execution unit. The names of these units do not constitute a limitation on the unit itself in some cases, and for example, the extracting unit may also be described as a unit that "extracts the target node information corresponding to the target client from the task creation request in response to detecting the task creation request issued by the target client".

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be understood by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of technical features, but encompasses other technical features formed by any combination of technical features or their equivalents without departing from the spirit of the invention. Such as a solution in which features and technical features having similar functions (but not limited to) disclosed in the embodiments of the present disclosure are replaced with each other.

Claims

1. A task creation request processing method, comprising:

responding to a task creation request sent by a target client, and extracting target node information corresponding to the target client from the task creation request, wherein the task creation request comprises target node information, the target node information comprises target node identification information and father node identification information, the target node identification information is node identification information of a network node where the target client is located in an internal network, and the father node identification information included in the target node information is node identification information of a father level network node of the network node represented by the target node identification information;

according to the target node information, performing superior node query processing on an organization node information set corresponding to the target node information to obtain each organization node information as a superior node information set;

for each upper node information in the set of upper node information, performing the creating step of:

in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the virtual task information set corresponding to the upper node information, performing the following steps:

Determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified;

performing state verification on the determined task information to be verified to obtain target task information;

generating detailed information of each task according to the target task information;

adding each of the generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set;

and displaying the updated task detail information set on the display equipment corresponding to the target client.

2. The method of claim 1, wherein the performing, according to the target node information, a superior node query process on an organization node information set corresponding to the target node information, to obtain each organization node information as a superior node information set, includes:

determining parent node identification information included in the target node information as target parent node identification information;

based on the target parent node identification information, the following node query steps are performed:

selecting organization node information meeting parent node conditions from the organization node information set according to the target parent node identification information;

In response to determining that the selected organization node information includes organization parent node identification information, determining the organization parent node identification information included in the determined organization node information as target parent node identification information and performing the node querying step again;

the selected individual organization node information is determined as a set of upper level node information.

3. The method according to claim 2, wherein the performing the state verification on the determined task information to be verified to obtain the target task information includes:

for each piece of task information to be verified in the pieces of task information to be verified, executing the following verification steps:

determining the task information to be verified as invalid task information in response to determining that the task issuing state corresponding to the task information to be verified does not meet the task state condition;

in response to determining that the task information to be verified does not meet a task time condition, determining the task information to be verified as invalid task information;

and determining the task information to be verified as target task information in response to determining that the task issuing state corresponding to the task information to be verified meets the task state condition and the task information to be verified meets the task time condition.

4. A method according to claim 3, wherein the target task information includes task identification information, issuing node identification information, initiating node identification information, index set identification information, task creation time, task deadline, and task description text information; and

and generating detailed information of each task according to the target task information, wherein the detailed information comprises the following steps:

for each of the respective target task information, performing the steps of:

in response to determining that task detail information corresponding to the target task information exists in a task detail information set corresponding to the target node information, determining the target task information as invalid task information;

generating each task index information according to index set identification information included in the target task information;

and determining task identification information, issuing node identification information, initiating node identification information, task creation time, task expiration time and task description text information included in the task index information and the target task information as task detail information.

5. The method of claim 4, wherein the method further comprises:

Responding to a task release request sent by the target client, and acquiring target node information corresponding to the target client;

in response to determining that the obtained target node information satisfies the publishing node condition, performing the task publishing step of:

extracting issuing task information, issuing task index information and task state information from the task issuing request;

generating a task issuing deadline according to the task issuing information and a preset task period;

generating issuing index set identification information according to the issuing task index information;

generating task description text information according to the issuing task information, the issuing task index information and the issuing task deadline;

determining virtual task information according to the issuing task information, the task description text information, the issuing index set identification information, the target node information and the issuing task deadline;

adding the determined virtual task information to a virtual task information set corresponding to the target node information, so as to enable each client corresponding to each organization node information meeting the lower node condition in the organization node information set to generate task detail information;

And updating the task issuing state corresponding to the generated virtual task information according to the task state information.

6. A task creation request processing device comprising:

an extracting unit configured to extract target node information corresponding to a target client from a task creation request in response to detection of the task creation request sent by the target client, wherein the task creation request includes target node information including target node identification information and parent node identification information, the target node identification information is node identification information of a network node where the target client is located in an internal network, and the parent node identification information included in the target node information is node identification information of a parent network node of the network node characterized by the target node identification information;

the processing unit is configured to perform superior node query processing on the organization node information set corresponding to the target node information according to the target node information to obtain each organization node information as a superior node information set;

an execution unit configured to execute, for each upper node information in the upper node information set, the following creation step: in response to determining that at least one piece of virtual task information corresponding to the target node information exists in the virtual task information set corresponding to the upper node information, performing the following steps: determining each piece of virtual task information in the at least one piece of virtual task information as task information to be verified; performing state verification on the determined task information to be verified to obtain target task information; generating detailed information of each task according to the target task information; adding each of the generated task detail information to a task detail information set corresponding to the target node information to update the task detail information set; and displaying the updated task detail information set on the display equipment corresponding to the target client.

7. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-5.

8. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1-5.