CN116384945B - Project management method and system - Google Patents
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Abstract
The application provides a project management method and a project management system, comprising the following steps: acquiring a project approval document of a project to be managed; acquiring a characteristic legend corresponding to an item to be managed according to the item approval structured data, the item approval acquisition data and the item approval stage indication data, wherein the characteristic legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information; inputting the feature legend into a project management model, extracting corresponding project features by the project management model according to node information, relation information and stage indication information in the feature legend, and outputting corresponding project management results according to the project features, wherein the project management model is trained by utilizing a plurality of feature legend samples with project management result labels. The scheme can be applied to various approval scenes, so that the approval efficiency can be improved, and the approval accuracy is ensured.
Description
Technical Field
The application relates to the technical field of project management, in particular to a project management method and system.
Background
With the popularization of paperless and intelligent offices, the requirements on project management are also continuously improved. Project management is an emerging management discipline based on modern management, and integrates financial control, talent resource management, risk control, quality management, information technology management (communication management), purchase management and the like in enterprise management effectively, so as to achieve the purposes of high efficiency, high quality and low cost of completing various works or projects inside an enterprise. In the face of the complex state of multi-thread operation of project management, a large number of on-line project management systems are developed, and basically are designed from management objects or realization layers for improving management efficiency, realizing functions of data information sharing and the like.
At present, the conventional project management process generally includes that an approved party of project management in a project participant inputs approval information at a preset approval interface, and then the approved party of the project management performs approval to give project approval results.
Disclosure of Invention
The embodiment of the application provides a project management method and system, which are used for solving the technical problems of low project management efficiency and strong subjectivity in the prior art.
In a first aspect, an embodiment of the present application provides a method for managing items, including:
acquiring a project approval document of a project to be managed, wherein the project approval document comprises project approval structural data, project approval acquisition data and project approval stage indication data, the project approval structural data is used for indicating approval nodes and approval sequences related in the project to be managed, and the project approval acquisition data is data input by a project participant;
acquiring a characteristic legend corresponding to an item to be managed according to the item approval structured data, the item approval acquisition data and the item approval stage indication data, wherein the characteristic legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information;
inputting the feature legend into a project management model, extracting corresponding project features by the project management model according to node information, relation information and stage indication information in the feature legend, and outputting corresponding project management results according to the project features, wherein the project management model is trained by utilizing a plurality of feature legend samples with project management result labels.
In an optional embodiment of the present application, according to project approval structured data, project approval collection data, and project approval stage indication data, obtaining a feature legend corresponding to a project to be managed includes:
respectively carrying out entity word recognition on a text corresponding to the project approval structured data, a text corresponding to the project approval acquisition data and a text corresponding to the project approval stage indication data to obtain a corresponding structured data entity word, an acquisition data entity word and a stage data entity word;
determining relation information among a plurality of approval nodes and each approval node according to the structured data entity words, and constructing a first legend frame according to the plurality of approval nodes, the relation information among each approval node and one approval stage node;
determining approval stage indication information according to the stage data entity words, and adding the approval stage indication information to approval stage nodes in the first legend frame to obtain a second legend frame;
and determining corresponding node information of each approval node according to the structured data entity words and the acquired data entity words, and respectively adding the node information to the corresponding approval nodes in the second legend frame to obtain the characteristic legend.
In an alternative embodiment of the present application, determining approval stage indication information according to the stage data entity word, adding the approval stage indication information to the approval stage node in the first legend frame to obtain a second legend frame, including:
determining a plurality of approval stages included in the item to be managed and approval nodes corresponding to the approval stages according to the structured data entity words, and determining the current approval stage of the item to be managed according to approval stage indication information;
and adding approval stage indication information to approval stage nodes in the first legend frame, and deleting approval nodes which do not belong to the current approval stage in the first legend frame to obtain a second legend frame.
In an alternative embodiment of the application, the method further comprises:
if the node information of any examination node in the feature legend is empty or obvious errors exist, interpolation is carried out according to the node information of other examination nodes except any examination node in the feature legend and the relation information among all examination nodes, so that target node information of any examination node is obtained;
and replacing node information of any trial node by utilizing the target node information to obtain a new feature legend, wherein the new feature legend is used for acquiring a project management result of a project to be managed.
In an optional embodiment of the present application, interpolating according to node information of other approval nodes except any approval node in the feature legend and relationship information between the approval nodes to obtain target node information of any approval node, including:
and acquiring target node information corresponding to any examination node according to node information of front and back examination nodes of any examination node and relation information between any examination node and the front and back examination nodes, wherein the front and back examination nodes are examination nodes adjacent to any examination node in time sequence.
In an alternative embodiment of the application, the project approval document further includes project approval result data;
the method further comprises the steps of:
acquiring a corresponding project approval result according to the project approval result data;
after the project management result is obtained, comparing the project management result with the project approval result, and if the project management result and the project approval result are not matched, determining suspicious approval nodes based on the feature legend.
In an alternative embodiment of the present application, obtaining a corresponding project approval result according to project approval result data includes:
and carrying out entity word recognition on the text corresponding to the project approval result data to obtain corresponding project approval entity words, and obtaining project approval results based on the project approval entity words.
In a second aspect, an embodiment of the present application provides an item management system, including:
the project approval document acquisition module is used for acquiring a project approval document of a project to be managed, wherein the project approval document comprises project approval structured data, project approval acquisition data and project approval stage indication data, the project approval structured data is used for indicating approval nodes and approval orders related in the project to be managed, and the project approval acquisition data is data input by a project participant;
the characteristic legend acquisition module is used for acquiring a characteristic legend corresponding to the item to be managed according to the item approval structured data, the item approval acquisition data and the item approval stage indication data, wherein the characteristic legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information;
the project management result acquisition module is used for inputting the feature legend into a project management model, extracting corresponding project features by the project management model according to node information, relation information and stage indication information in the feature legend, and outputting corresponding project management results according to the project features, wherein the project management model is trained by utilizing a plurality of feature legend samples with project management result labels.
In an alternative embodiment of the present application, the feature legend acquisition module is specifically configured to:
respectively carrying out entity word recognition on a text corresponding to the project approval structured data, a text corresponding to the project approval acquisition data and a text corresponding to the project approval stage indication data to obtain a corresponding structured data entity word, an acquisition data entity word and a stage data entity word;
determining relation information among a plurality of approval nodes and each approval node according to the structured data entity words, and constructing a first legend frame according to the plurality of approval nodes, the relation information among each approval node and one approval stage node;
determining approval stage indication information according to the stage data entity words, and adding the approval stage indication information to approval stage nodes in the first legend frame to obtain a second legend frame;
and determining corresponding node information of each approval node according to the structured data entity words and the acquired data entity words, and respectively adding the node information to the corresponding approval nodes in the second legend frame to obtain the characteristic legend.
In an alternative embodiment of the present application, the feature legend acquisition module is further configured to:
determining a plurality of approval stages included in the item to be managed and approval nodes corresponding to the approval stages according to the structured data entity words, and determining the current approval stage of the item to be managed according to approval stage indication information;
And adding approval stage indication information to approval stage nodes in the first legend frame, and deleting approval nodes which do not belong to the current approval stage in the first legend frame to obtain a second legend frame.
In an alternative embodiment of the present application, the apparatus further includes an interpolation processing module for:
if the node information of any examination node in the feature legend is empty or obvious errors exist, interpolation is carried out according to the node information of other examination nodes except any examination node in the feature legend and the relation information among all examination nodes, so that target node information of any examination node is obtained;
and replacing node information of any trial node by utilizing the target node information to obtain a new feature legend, wherein the new feature legend is used for acquiring a project management result of a project to be managed.
In an alternative embodiment of the present application, the interpolation processing module is specifically configured to:
and acquiring target node information corresponding to any examination node according to node information of front and back examination nodes of any examination node and relation information between any examination node and the front and back examination nodes, wherein the front and back examination nodes are examination nodes adjacent to any examination node in time sequence.
In an alternative embodiment of the application, the project approval document further includes project approval result data;
the device also comprises a project management result comparison module for:
acquiring a corresponding project approval result according to the project approval result data;
after the project management result is obtained, comparing the project management result with the project approval result, and if the project management result and the project approval result are not matched, determining suspicious approval nodes based on the feature legend.
In an alternative embodiment of the present application, the project management result comparison module is specifically configured to:
and carrying out entity word recognition on the text corresponding to the project approval result data to obtain corresponding project approval entity words, and obtaining project approval results based on the project approval entity words.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor;
a memory having a computer program stored therein;
a processor for executing a computer program to implement the method provided in the first aspect embodiment or any of the alternative embodiments of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium having a computer program stored thereon, which when executed by a processor implements the method provided in the embodiment of the first aspect or any of the alternative embodiments of the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions are read from a computer readable storage medium by a processor of a computer device, which processor executes the computer instructions such that the computer device, when executed, implements the method provided in the embodiment of the first aspect or any alternative embodiment of the first aspect.
The technical scheme provided by the application has the beneficial effects that:
according to project approval structured data, project approval acquisition data and project approval stage indication data of a project to be managed, a feature legend of the project to be managed is obtained, so that the feature legend is a structure diagram comprising an approval stage node and a plurality of approval nodes, the approval stage node comprises corresponding approval stage indication information, the approval node comprises corresponding node information, and the diagram also comprises relation information among the approval nodes. And then inputting the characteristic legend into a preset project approval model, and processing the characteristic legend through the model to output project management results of the project to be managed.
Benefits of one or more other aspects of this approach will be described in the detailed description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings that are required to be used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 is a schematic flow chart of a project management method according to an embodiment of the present application;
FIG. 2 is an example of a feature diagram of an item to be managed according to an embodiment of the present application;
fig. 3 is a flow chart of a method for determining suspicious examination nodes according to an embodiment of the present application;
FIG. 4 is a block diagram of a project management system according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described below with reference to the drawings in the present application. It should be understood that the embodiments described below with reference to the drawings are exemplary descriptions for explaining the technical solutions of the embodiments of the present application, and the technical solutions of the embodiments of the present application are not limited.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and "comprising," when used in this specification, specify the presence of stated features, information, data, steps, operations, elements, and/or components, but do not preclude the presence or addition of other features, information, data, steps, operations, elements, components, and/or groups thereof, all of which may be included in the present specification. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein indicates that at least one of the items defined by the term, e.g., "a and/or B" may be implemented as "a", or as "B", or as "a and B".
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.
Fig. 1 is a flow chart of a project management method according to an embodiment of the present application, as shown in fig. 1, the method may include:
step S101, a project approval document of a project to be managed is obtained, the project approval document comprises project approval structural data, project approval collection data and project approval stage indication data, the project approval structural data are used for indicating approval nodes and approval orders related in the project to be managed, and the project approval collection data are data input by a project participant.
The approval document of the project to be managed is derived from an approval program corresponding to the project to be managed, and can be obtained based on the source code of the approval program and the currently stored operation log. But may also be written manually based on the approval of the current item.
The project approval structured data refers to data for describing project approval flows, which describe steps required to be undergone by project type approval corresponding to the project to be managed, and time sequence relationships, logic relationships and the like among the steps. Each step is also described as approving or not passing the corresponding approval rule.
The project approval collection data are data input by participants of the project to be managed, each approval step can require corresponding data as an approval object, and the data can be input by the participants of the project in a text mode or in an option selection mode. Specifically, the embodiment of the application can provide an approval information input interface, the information which needs to be input by the participants in each step is given in the interface, and the participants can input related information according to guidance.
Before the project approval is finished, one project to be managed may include a plurality of project approval stages, and for each project under approval or already approved, the project approval stage where the project is currently located may be acquired. For example, the approval process of a certain item to be managed includes an approval stage 1, an approval stage 2, and an approval stage 3 in sequence, wherein if the item to be managed is currently in the approval stage 3, the approval of the item to be managed is ended, and if the item to be managed is in the approval stage 1 or the approval stage 2, the item to be managed is identified as being in progress. It will be appreciated that each project approval stage includes a different number of approval steps, with the later project approval stages including a greater number of steps.
Specifically, at the current moment, in order to manage the project to be managed, a project approval document of the project to be managed needs to be acquired, and project approval stage indication data, project approval structural data and project approval collection data corresponding to the project approval document are acquired from the project approval document.
Step S102, according to project approval structured data, project approval acquisition data and project approval stage indication data, a feature legend corresponding to a project to be managed is obtained, wherein the feature legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information.
The foregoing description shows that, according to the project approval structural data, the relationships between the project approval steps and the approval steps can be determined, so that each approval step can correspond to one approval node, and further the relationships between the approval nodes can be obtained. The relationship among each approval node comprises a time sequence relationship, a logic relationship and the like.
Specifically, in order to obtain the project management structure of the project to be managed by using an AI (artificial intelligence) model, the project to be managed may be converted into a feature legend, where the feature legend may be understood as an image, and the image includes a plurality of approval nodes and relationship information between the approval nodes, and each of the approval nodes carries node information thereof. Specifically, the project approval structured data, the project approval acquisition data and the project approval stage indication data are analyzed to determine nodes in the characteristic legend, wherein the nodes comprise an approval stage node and a plurality of approval nodes, and meanwhile, approval stage indication information contained in the approval stage node is determined, and node information contained in the approval node is determined. For example, approval stage indication information may be represented by a specific numerical value, "1" indicating that the first approval stage is in progress, "2" indicating that the second approval stage is in progress, and "3" indicating that the third approval stage is in progress. The node information can also be represented by a number, wherein "0" indicates that the corresponding approval node (i.e. the approval step) does not pass the approval, and "1" indicates that the corresponding approval node passes the approval, and of course, the node information not only contains the information about whether the approval passes or not, but also can contain other types of information, that is, the node information can be multidimensional and can be set according to actual requirements. In addition, the relationship information between the approval nodes can be represented by arrowed lines. As shown in fig. 2, in one feature map example, there are 4 approval nodes (nodes 1, 2, 3, 4) and one approval stage node 5.
Step S103, inputting a feature legend into a project management model, extracting corresponding project features by the project management model according to node information, relation information and stage indication information in the feature legend, and outputting corresponding project management results according to the project features, wherein the project management model is trained by utilizing a plurality of feature legend samples with project management result labels.
The project management model may be a preset image processing model, and the model may include a plurality of convolution layers for feature extraction or neural network layers for other image feature extraction. In the process of processing the feature legend by the model, each node in the legend can be regarded as a pixel point, the node information is regarded as a pixel value, and meanwhile, the relation information among the nodes is regarded as the relation information among the pixel points. The input of the model is the characteristic legend of the project to be managed, and the output is the project management result of the project to be managed. The project management result may be that the project approval passes or the project approval does not pass, etc.
Specifically, the feature legend obtained in the previous step is input into an input project management model which is obtained through training in advance, the model performs feature extraction based on information contained in the feature map to obtain corresponding project features, and then a corresponding project management result is output based on the project features.
It should be noted that, the scheme can be applied to various different scenes, namely, one is "intelligent approval without intelligence", namely, the project management result obtained by the scheme is fed back to the project participants as a final result, the other is "approval result monitoring", the project management result obtained by the scheme is compared with the project management result obtained by manual approval, if the project management result is matched with the project management result, the project participants are fed back, and if the project management result is not matched with the project management result, the incorrect approval nodes are required to be searched and fed back to the project participants.
According to the scheme provided by the application, the characteristic legend of the item to be managed is obtained according to the item approval structured data, the item approval acquisition data and the item approval stage indication data of the item to be managed, so that the characteristic legend is a structure diagram comprising an approval stage node and a plurality of approval nodes, the approval stage node comprises corresponding approval stage indication information, the approval node comprises corresponding node information, and the diagram also comprises relation information among the approval nodes. And then inputting the characteristic legend into a preset project approval model, and processing the characteristic legend through the model to output project management results of the project to be managed.
In an optional embodiment of the present application, according to project approval structured data, project approval collection data, and project approval stage indication data, obtaining a feature legend corresponding to a project to be managed includes:
respectively carrying out entity word recognition on a text corresponding to the project approval structured data, a text corresponding to the project approval acquisition data and a text corresponding to the project approval stage indication data to obtain a corresponding structured data entity word, an acquisition data entity word and a stage data entity word;
determining relation information among a plurality of approval nodes and each approval node according to the structured data entity words, and constructing a first legend frame according to the plurality of approval nodes, the relation information among each approval node and one approval stage node;
determining approval stage indication information according to the stage data entity words, and adding the approval stage indication information to approval stage nodes in the first legend frame to obtain a second legend frame;
and determining corresponding node information of each approval node according to the structured data entity words and the acquired data entity words, and respectively adding the node information to the corresponding approval nodes in the second legend frame to obtain the characteristic legend.
Specifically, after a text corresponding to project approval structured data, a text corresponding to project approval collection data and a text corresponding to project approval stage indication data are obtained, word segmentation processing entity word recognition is performed on each text, and then corresponding structured data entity words, collection data entity words and stage data entity words are obtained.
Firstly, analyzing and processing structured data entity words, and obtaining how many approval stages and how many approval nodes are included in the item to be managed, and obtaining the relationship among the approval nodes, so that a first legend frame can be constructed according to the approval nodes, the relationship among the approval nodes and one approval stage node, and it can be understood that the first legend frame contains all the approval nodes in the item to be managed, no corresponding node information is added in the approval nodes, and no corresponding approval stage indication information is added in the approval stage nodes.
Then, determining approval stage indication information according to the stage entity words, adding the approval stage indication information to approval stage nodes in a first legend frame, and meanwhile, as known from the foregoing description, the number of approval nodes corresponding to each approval stage is different, so that a plurality of approval stages included in the item to be managed and approval nodes corresponding to each approval stage are required to be determined according to the structured data entity words, and determining the current approval stage in which the item to be managed is located according to the approval stage indication information; and adding the approval stage indication information to the approval stage nodes in the first legend frame, deleting the approval nodes which do not belong to the current approval stage in the first legend frame, and obtaining the second legend frame.
And finally, determining corresponding node information of each approval node according to the structured data entity words and the collected data entity words, and respectively adding the node information to the corresponding approval nodes in the second legend frame to obtain the characteristic legend.
It should be noted that, when the feature legend of the item to be managed is constructed, the approval stage node may be set to be connected with each approval node through a line segment, or may be connected with only one of the approval stages nodes through a line segment.
In an alternative embodiment of the present application, the method may further comprise:
if the node information of any examination and approval node in the feature legend is determined to be empty or obvious errors exist, interpolation is carried out according to the node information of other examination and approval nodes except any examination and approval node in the feature legend and the relation information among all examination and approval nodes, so that target node information of any examination and approval node is obtained;
and replacing the node information of any trial node by using the target node information to obtain a new feature legend, wherein the new feature legend is used for obtaining the project management result of the project to be managed.
Specifically, after the feature legend of the item to be managed is obtained, there may be a situation that node information of a certain approval node is empty or there is a significant error, and at this time, the node information of the approval node is not available. As can be seen from the foregoing description, the approval node corresponds to a pixel in the image, and thus the node information of the approval node can be retrieved based on the interpolation principle. Different from interpolation in the image, the interpolation processing in the application is carried out based on the node information of other approval nodes except any approval node in the characteristic legend and the relation information among all the approval nodes, thereby ensuring the accuracy of the node information obtained by interpolation.
Specifically, interpolation is performed according to node information of other approval nodes except any approval node in the feature legend and relation information among all approval nodes, so as to obtain target node information of any approval node, including: and acquiring target node information corresponding to any examination node according to node information of front and back examination nodes of any examination node and relation information between any examination node and the front and back examination nodes, wherein the front and back examination nodes are examination nodes adjacent to any examination node in time sequence.
In an alternative embodiment of the present application, the project approval document further includes project approval result data;
the method may further comprise:
acquiring a corresponding project approval result according to the project approval result data;
after the project management result is obtained, comparing the project management result with the project approval result, and if the project management result and the project approval result are not matched, determining suspicious approval nodes based on the characteristic legend.
The method for obtaining the corresponding project approval result according to the project approval result data comprises the following steps: and carrying out entity word recognition on the text corresponding to the project approval result data to obtain corresponding project approval entity words, and obtaining project approval results based on the project approval entity words.
Specifically, in the foregoing "approval result monitoring" scenario, after the model management result of the item to be managed is obtained, the model management result may be compared with the item approval result, and if the model management result is not matched with the item approval result, it is indicated that there may be an error. Then the suspicious node needs to be determined by further processing of the feature legend.
Specifically, as shown in fig. 3, the determination of suspicious nodes by further processing the feature legend includes:
Determining a target item approval stage from all item approval stages before the current item approval stage, wherein the last approval node on the time sequence corresponding to the target item approval stage has the most connecting line segments (comprising the sum of the line segments pointing to the target item approval stage and the line segments sent by the target item approval stage) in the last approval node on the time sequence corresponding to the current item approval stage;
returning the feature legend to a first feature legend corresponding to the target item approval stage, namely deleting approval nodes which do not belong to the target item approval stage in the feature legend, and updating approval stage indication information of the approval stage nodes to be approval stage knowledge information corresponding to the target item approval stage;
and then, inputting the first characteristic legend into an item approval model, outputting a corresponding first item management result, and comparing the first item management result with an approval result corresponding to a target item approval stage.
If the first project management result is not matched with the approval result corresponding to the approval stage of the target project, all approval nodes corresponding to the approval stage of the target project are determined to be suspicious approval nodes, and if the first project management result is matched with the approval result, all approval nodes which can be deleted from the characteristic legend are determined to be suspicious approval nodes.
After the suspicious approval nodes are determined, the method can determine which one or more approval nodes have problems through manual screening and the like.
By the determination mode of the suspicious examination and approval node, the determination efficiency of the suspicious examination and approval node can be greatly improved.
Fig. 4 is a block diagram of a project management system according to an embodiment of the present application, and as shown in fig. 4, the apparatus 400 may include: a project approval document acquisition module 401, a feature legend acquisition module 402, and a project management result acquisition module 403, wherein,
the project approval document acquisition module 401 is configured to acquire a project approval document of a project to be managed, where the project approval document includes project approval structured data, project approval collection data, and project approval stage indication data, the project approval structured data is used to indicate approval nodes and approval orders involved in the project to be managed, and the project approval collection data is data input by a project participant;
the feature legend acquisition module 402 is configured to acquire a feature legend corresponding to an item to be managed according to the item approval structured data, the item approval acquisition data and the item approval stage indication data, where the feature legend includes an approval stage node, a plurality of approval nodes, and relationship information between the approval nodes, the approval nodes include corresponding node information, and the approval stage node includes corresponding approval stage indication information;
The project management result obtaining module 403 is configured to input a feature legend into a project management model, where the project management model is obtained by training a plurality of feature legend samples with project management result labels, and extracts corresponding project features according to node information, relationship information, and stage indication information in the feature legend, and outputs corresponding project management results according to the project features.
According to the scheme provided by the application, the characteristic legend of the item to be managed is obtained according to the item approval structured data, the item approval acquisition data and the item approval stage indication data of the item to be managed, so that the characteristic legend is a structure diagram comprising an approval stage node and a plurality of approval nodes, the approval stage node comprises corresponding approval stage indication information, the approval node comprises corresponding node information, and the diagram also comprises relation information among the approval nodes. And then inputting the characteristic legend into a preset project approval model, and processing the characteristic legend through the model to output project management results of the project to be managed.
In an alternative embodiment of the present application, the feature legend acquisition module is specifically configured to:
respectively carrying out entity word recognition on a text corresponding to the project approval structured data, a text corresponding to the project approval acquisition data and a text corresponding to the project approval stage indication data to obtain a corresponding structured data entity word, an acquisition data entity word and a stage data entity word;
determining relation information among a plurality of approval nodes and each approval node according to the structured data entity words, and constructing a first legend frame according to the plurality of approval nodes, the relation information among each approval node and one approval stage node;
determining approval stage indication information according to the stage data entity words, and adding the approval stage indication information to approval stage nodes in the first legend frame to obtain a second legend frame;
and determining corresponding node information of each approval node according to the structured data entity words and the acquired data entity words, and respectively adding the node information to the corresponding approval nodes in the second legend frame to obtain the characteristic legend.
In an alternative embodiment of the present application, the feature legend acquisition module is further configured to:
determining a plurality of approval stages included in the item to be managed and approval nodes corresponding to the approval stages according to the structured data entity words, and determining the current approval stage of the item to be managed according to approval stage indication information;
And adding approval stage indication information to approval stage nodes in the first legend frame, and deleting approval nodes which do not belong to the current approval stage in the first legend frame to obtain a second legend frame.
In an alternative embodiment of the present application, the apparatus further includes an interpolation processing module for:
if the node information of any examination node in the feature legend is empty or obvious errors exist, interpolation is carried out according to the node information of other examination nodes except any examination node in the feature legend and the relation information among all examination nodes, so that target node information of any examination node is obtained;
and replacing node information of any trial node by utilizing the target node information to obtain a new feature legend, wherein the new feature legend is used for acquiring a project management result of a project to be managed.
In an alternative embodiment of the present application, the interpolation processing module is specifically configured to:
and acquiring target node information corresponding to any examination node according to node information of front and back examination nodes of any examination node and relation information between any examination node and the front and back examination nodes, wherein the front and back examination nodes are examination nodes adjacent to any examination node in time sequence.
In an alternative embodiment of the application, the project approval document further includes project approval result data;
the device also comprises a project management result comparison module for:
acquiring a corresponding project approval result according to the project approval result data;
after the project management result is obtained, comparing the project management result with the project approval result, and if the project management result and the project approval result are not matched, determining suspicious approval nodes based on the feature legend.
In an alternative embodiment of the present application, the project management result comparison module is specifically configured to:
and carrying out entity word recognition on the text corresponding to the project approval result data to obtain corresponding project approval entity words, and obtaining project approval results based on the project approval entity words.
Referring now to fig. 5, a schematic diagram of an architecture of an electronic device (e.g., a terminal device or server performing the method of fig. 1) 500 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), wearable devices, and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 5 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
An electronic device includes: the memory is used for storing programs for executing the methods according to the method embodiments; the processor is configured to execute a program stored in the memory. Herein, the processor may be referred to as a processing device 501, which is described below, and the memory may include at least one of a Read Only Memory (ROM) 502, a Random Access Memory (RAM) 503, and a storage device 508, which are described below, specifically as follows:
as shown in fig. 5, the electronic device 500 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 501, which may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data required for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
In general, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 507 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 508 including, for example, magnetic tape, hard disk, etc.; and communication means 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 shows an electronic device 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.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or from the storage means 508, or from the ROM 502. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing device 501.
It should be noted that the computer readable storage medium described above in 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 of the foregoing. In the context of this 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 the present disclosure, however, the computer-readable signal medium may include 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 of the foregoing. 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 of the foregoing.
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 contained in the electronic device; or may exist alone without being incorporated into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a project approval document of a project to be managed, wherein the project approval document comprises project approval structural data, project approval acquisition data and project approval stage indication data, the project approval structural data is used for indicating approval nodes and approval sequences related in the project to be managed, and the project approval acquisition data is data input by a project participant; acquiring a characteristic legend corresponding to an item to be managed according to the item approval structured data, the item approval acquisition data and the item approval stage indication data, wherein the characteristic legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information; inputting the feature legend into a project management model, extracting corresponding project features by the project management model according to node information, relation information and stage indication information in the feature legend, and outputting corresponding project management results according to the project features, wherein the project management model is trained by utilizing a plurality of feature legend samples with project management result labels.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, 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 modules or units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The names of the modules or units are not limited to the unit itself in some cases, and for example, the interpolation processing module may be also described as a "module that performs interpolation processing".
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.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on 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 of the foregoing.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, a specific method implemented by the above-described computer readable medium when executed by an electronic device may refer to a corresponding procedure in the foregoing method embodiment, which is not described herein again.
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 appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).
Moreover, although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (7)
1. A method for project management, wherein the method is applied to an approval result monitoring scene, and comprises the following steps:
acquiring a project approval document of a project to be managed, wherein the project approval document comprises project approval structural data, project approval acquisition data and project approval stage indication data, the project approval structural data are used for indicating approval nodes, approval orders and approval rules which are related in the project to be managed and are approved or not passed by all the approval nodes, and the project approval acquisition data are data input by a project participant;
acquiring a characteristic legend corresponding to the item to be managed according to the item approval structured data, the item approval acquisition data and the item approval stage indication data, wherein the characteristic legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information;
Inputting the feature legend into a project management model, wherein the project management model extracts corresponding project features according to node information, the relation information and the stage indication information in the feature legend, and outputs corresponding project management results according to the project features, and the project management model is trained by utilizing a plurality of feature legend samples with project management result labels;
the project management model is a preset image processing model and comprises a plurality of convolution layers for feature extraction or neural network layers for extracting other image features;
inputting the feature legend into a project management model, wherein the project management model extracts corresponding project features according to node information, the relation information and the stage indication information in the feature legend, and the project management model comprises the following steps:
the project management model regards each node in the feature legend as a pixel point, regards node information as a pixel value, and simultaneously regards the relation information among the nodes as the relation information among the pixel points for processing to obtain the project feature;
the method further comprises the steps of:
if the node information of any examination and approval node in the feature legend is determined to be empty or obvious errors exist, interpolation is carried out according to the node information of other examination and approval nodes except any examination and approval node in the feature legend and the relation information among all examination and approval nodes, so that target node information of any examination and approval node is obtained;
The node information of any trial node is replaced by the target node information to obtain a new feature legend, and the new feature legend is used for obtaining a project management result of the project to be managed;
the project approval document also comprises project approval result data; the method further comprises the steps of:
acquiring a corresponding project approval result according to the project approval result data;
after the project management result is obtained, comparing the project management result with the project approval result, and if the project management result and the project approval result are not matched, determining suspicious approval nodes based on the characteristic legend.
2. The method of claim 1, wherein the obtaining the feature legend corresponding to the item to be managed according to the item approval structured data, the item approval collection data, and the item approval stage indication data includes:
respectively carrying out entity word recognition on a text corresponding to the project approval structured data, a text corresponding to the project approval acquisition data and a text corresponding to the project approval stage indication data to obtain a corresponding structured data entity word, an acquisition data entity word and a stage data entity word;
Determining a plurality of approval nodes and relation information among the approval nodes according to the structured data entity words, and constructing a first legend frame according to the plurality of approval nodes, the relation information among the approval nodes and an approval stage node;
determining the approval stage indication information according to the stage data entity words, and adding the approval stage indication information to the approval stage nodes in the first legend frame to obtain a second legend frame;
and determining corresponding node information of each approval node according to the structured data entity words and the acquired data entity words, and respectively adding the node information to the corresponding approval nodes in the second legend frame to obtain the characteristic legend.
3. The method of claim 2, wherein the determining the approval stage indication information according to the stage data entity word, adding the approval stage indication information to the approval stage node in the first legend frame, and obtaining a second legend frame includes:
determining a plurality of approval stages and approval nodes corresponding to the approval stages included in the item to be managed according to the structured data entity word, and determining a current approval stage in which the item to be managed is located according to the approval stage indication information;
And adding the approval stage indication information to the approval stage nodes in the first legend frame, deleting the approval nodes which do not belong to the current approval stage in the first legend frame, and obtaining the second legend frame.
4. The method of claim 1, wherein the obtaining the corresponding project approval result according to the project approval result data comprises:
and carrying out entity word recognition on the text corresponding to the item approval result data to obtain corresponding item approval entity words, and acquiring the item approval result based on the item approval entity words.
5. A project management system, wherein the system is applied to an approval result monitoring scenario, comprising:
the project approval document acquisition module is used for acquiring project approval documents of a project to be managed, wherein the project approval documents comprise project approval structured data, project approval acquisition data and project approval stage indication data, the project approval structured data are used for indicating approval nodes, approval orders and approval rules of each approval node, which are related in the project to be managed, pass or fail, and the project approval acquisition data are data input by a project participant;
The characteristic legend acquisition module is used for acquiring a characteristic legend corresponding to the item to be managed according to the item approval structural data, the item approval acquisition data and the item approval stage indication data, wherein the characteristic legend comprises an approval stage node, a plurality of approval nodes and relation information among the approval nodes, the approval nodes comprise corresponding node information, and the approval stage node comprises corresponding approval stage indication information;
the project management result acquisition module is used for inputting the characteristic legend into a project management model, extracting corresponding project characteristics according to node information, the relation information and the stage indication information in the characteristic legend by the project management model, and outputting corresponding project management results according to the project characteristics, wherein the project management model is trained by utilizing a plurality of characteristic legend samples with project management result labels;
the project management model is a preset image processing model and comprises a plurality of convolution layers for feature extraction or neural network layers for extracting other image features;
inputting the feature legend into a project management model, wherein the project management model extracts corresponding project features according to node information, the relation information and the stage indication information in the feature legend, and the project management model comprises the following steps:
The project management model regards each node in the feature legend as a pixel point, regards node information as a pixel value, and simultaneously regards the relation information among the nodes as the relation information among the pixel points for processing to obtain the project feature;
the device also comprises an interpolation processing module for:
if the node information of any examination and approval node in the feature legend is determined to be empty or obvious errors exist, interpolation is carried out according to the node information of other examination and approval nodes except any examination and approval node in the feature legend and the relation information among all examination and approval nodes, so that target node information of any examination and approval node is obtained;
the node information of any trial node is replaced by the target node information to obtain a new feature legend, and the new feature legend is used for obtaining a project management result of the project to be managed;
the project approval document also comprises project approval result data; the device also comprises a project management result comparison module for:
acquiring a corresponding project approval result according to the project approval result data;
after the project management result is obtained, comparing the project management result with the project approval result, and if the project management result and the project approval result are not matched, determining suspicious approval nodes based on the characteristic legend.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory, characterized in that the processor executes the computer program to carry out the steps of the method according to any one of claims 1-4.
7. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-4.
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