CN117149211A - Workflow distance measurement method, device, equipment and storage medium - Google Patents
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Abstract
The application discloses a method, a device, equipment and a storage medium for measuring a workflow distance, which can be applied to the field of big data or the field of finance. The method comprises the following steps: acquiring a first workflow and a second workflow; converting the first workflow and the second workflow into a tree structure respectively; sequentially calculating the first workflow structure tree and the second workflow structure tree by using the echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree; and determining the distance between the first workflow and the second workflow according to the state values of the two initial flow nodes. Through the method, the workflow is displayed in the form of a tree structure, the structural characteristics of the workflow are met, and the thought based on the model space and the processing method of the echo state network are used, so that the workflow is instantiated in the model space, and the purpose of distance measurement is achieved.
Description
Technical Field
The present application relates to the field of big data or the field of financial technologies, and in particular, to a method, an apparatus, a device, and a storage medium for measuring a workflow distance.
Background
Workflow multiplexing refers to the process of modifying a workflow model that already exists and is similar to the user's needs to meet new application needs. Workflow multiplexing can improve the design efficiency and quality of the workflow. However, the workflow is complicated in flow chart, so that the workflow cannot be digitized by semantic analysis, and therefore, the workflow distance measurement cannot be realized.
Disclosure of Invention
In view of this, the embodiments of the present application provide a method, an apparatus, a device, and a storage medium for measuring a workflow distance, which aim to implement the workflow distance measurement.
In a first aspect, an embodiment of the present application provides a method for measuring a workflow distance, including:
acquiring a first workflow and a second workflow;
converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree;
sequentially calculating the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree;
and determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree.
Optionally, the process of converting the workflow into a tree structure includes:
determining the connection sequence between each flow node in the workflow;
deleting reverse connection among the flow nodes, and deleting the end flow nodes;
when two process nodes point to the same target process node at the same time, copying the target process node to serve as child nodes of the two process nodes respectively;
and taking the flow nodes and the connection sequence among the flow nodes as a workflow structure tree.
Optionally, the process of calculating the workflow structure tree by using the echo state network to obtain the state value of the initial flow node in the workflow structure tree is as follows:
defining flow node data characteristic values for each flow node in the workflow structure tree;
and calculating the state value of the initial flow node based on an echo state calculation formula by utilizing the flow node data characteristic value.
Optionally, the determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree includes:
and determining a target distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree by using a Euclidean distance calculation formula.
In a second aspect, an embodiment of the present application provides a workflow distance measurement apparatus, where the apparatus includes:
the acquisition module is used for acquiring the first workflow and the second workflow;
the conversion module is used for converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree;
the computing module is used for sequentially computing the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree;
and the measurement module is used for determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree.
Optionally, the conversion module is specifically configured to:
determining the connection sequence between each flow node in the workflow;
deleting reverse connection among the flow nodes, and deleting the end flow nodes;
when two process nodes point to the same target process node at the same time, copying the target process node to serve as child nodes of the two process nodes respectively;
and taking the flow nodes and the connection sequence among the flow nodes as a workflow structure tree.
Optionally, the computing module is specifically configured to:
defining flow node data characteristic values for each flow node in the workflow structure tree;
and calculating the state value of the initial flow node based on an echo state calculation formula by utilizing the flow node data characteristic value.
Optionally, the measurement module is specifically configured to:
and determining a target distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree by using a Euclidean distance calculation formula.
In a third aspect, an embodiment of the present application provides an apparatus, the apparatus including a memory for storing instructions or code, and a processor for executing the instructions or code to cause the apparatus to perform the method of measuring workflow distance according to any one of the first aspects.
In a fourth aspect, embodiments of the present application provide a computer storage medium having code stored therein, which when executed, implements a method of measuring workflow distance according to any of the first aspects.
The embodiment of the application provides a method, a device, equipment and a storage medium for measuring a workflow distance. When the method is executed, a first workflow and a second workflow are acquired first; then, converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree; sequentially calculating the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree; and finally, determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree. In this way, the workflow is displayed in the form of a tree structure, the structural characteristics of the workflow are met, and the thought based on a model space and the processing method of the echo state network are used, so that the workflow is instantiated in the model space, and the purpose of distance measurement is achieved.
Drawings
In order to more clearly illustrate this embodiment or the technical solutions of the prior art, the drawings that are required for the description of the embodiment or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for measuring a workflow distance according to an embodiment of the present application;
FIG. 2 is a flow chart of a workflow provided by an embodiment of the present application;
FIG. 3 is a flow chart of another workflow provided by an embodiment of the present application;
FIG. 4 is a flow chart of yet another workflow provided by an embodiment of the present application;
FIG. 5 is a schematic diagram of a workflow structure tree according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a workflow distance measuring device according to an embodiment of the present application.
Detailed Description
Workflow multiplexing refers to the process of modifying a workflow model that already exists and is similar to the user's needs to meet new application needs. Workflow multiplexing can improve the design efficiency and quality of the workflow. However, the workflow is complicated in flow chart, so that the workflow cannot be digitized by semantic analysis, and therefore, the workflow distance measurement cannot be realized.
Aiming at the technical problems, the embodiment of the application provides a method, a device, equipment and a storage medium for measuring the workflow distance. When the method is executed, a first workflow and a second workflow are acquired first; then, converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree; sequentially calculating the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree; and finally, determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree. In this way, the workflow is displayed in the form of a tree structure, the structural characteristics of the workflow are met, and the thought based on a model space and the processing method of the echo state network are used, so that the workflow is instantiated in the model space, and the purpose of distance measurement is achieved.
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
The method, the device, the equipment and the storage medium for measuring the workflow distance can be used in the financial field or other fields, for example, can be used in banking application scenes in the financial field. Other fields are any field other than the financial field, for example, the big data field. The foregoing is merely an example, and the application fields of the workflow distance measuring method, the workflow distance measuring device, the workflow distance measuring equipment and the storage medium provided by the application are not limited.
It should be apparent that the described embodiments of the application are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
As shown in fig. 1, fig. 1 is a flowchart of a workflow distance measurement method according to an embodiment of the present application, where the method may be applied to a terminal. In this embodiment, for ease of understanding, the description is given in connection with a terminal device capable of installing an application program. Those skilled in the art will appreciate that the terminal device may include, but is not limited to, mobile terminal devices such as smartphones, smart wearable devices, tablet computers, personal digital assistants, electronic book readers, laptop and desktop computers, and the like. The method comprises the following steps:
s101: a first workflow and a second workflow are acquired.
A workflow is an abstract, generalized description of business rules between the workflow and its operational steps. As shown in fig. 2, fig. 2 is a flowchart of a workflow provided in an embodiment of the present application. Fig. 2 includes a plurality of flow nodes, and the flow nodes are connected according to a step sequence. The logic and rules of how the work in the workflow is organized together in tandem can be represented in the computer by an appropriate model and calculated for implementation by the workflow. The main problems to be solved by the workflow are: to achieve a certain business objective, a computer is used to automatically communicate among a plurality of participants according to a certain predetermined rule.
S102: and converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree.
By exposing the workflow in the form of a tree structure, the attributes of each node in the workflow can be digitized.
In an embodiment of the present application, the process of converting a workflow into a tree structure includes:
determining the connection sequence between each flow node in the workflow;
deleting reverse connection among the flow nodes, and deleting the end flow nodes;
when two process nodes point to the same target process node at the same time, copying the target process node to serve as child nodes of the two process nodes respectively;
and taking the flow nodes and the connection sequence among the flow nodes as a workflow structure tree.
As shown in fig. 2, each flow node and the connection order can be determined according to the flow chart of the workflow. There may be a bi-directional connection between the flow nodes, such as flow node 4 and flow node 10 in fig. 2. The reverse deletion between the flow nodes in fig. 2 is required, and the end flow node is deleted at the same time, so as to obtain the flow chart shown in fig. 3. Then, the target flow node, i.e. the flow node to which both flow nodes point at the same time, is determined, such as flow node 10 and flow node 15 in fig. 3. The flow nodes are duplicated and respectively serve as child nodes of the two flow nodes, so that a flow chart as shown in fig. 4 is obtained. Finally, the flow nodes and the connection sequence between the flow nodes are used as a workflow structure tree, as shown in fig. 5.
S103: and c, sequentially calculating the first workflow structure tree and the second workflow structure tree to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree.
The solar state network is also called reservoir computation (RC, reservoir computino), which uses a reservoir of neurons from a randomly generated connected fixed internal weight matrix as a hidden layer to project the input into a high-dimensional, non-linear representation. The ESN generates hidden layer weights of the neural network in advance instead of training, and the hidden layer weight training is carried out separately from the hidden layer weight training to the output layer weight training, and the basic idea is that the generated reserve pool has a good attribute, and the reserve pool can be ensured to obtain good performance by training the weight from the reserve pool to the output layer by adopting a linear method.
In the embodiment of the application, the process of calculating the workflow structure tree by using the echo state network to obtain the state value of the initial flow node in the workflow structure tree is as follows:
defining flow node data characteristic values for each flow node in the workflow structure tree;
and calculating the state value of the initial flow node based on an echo state calculation formula by utilizing the flow node data characteristic value.
The node data characteristic values include task ID, task type, processor ID, task complexity and node processing time. The node data characteristic values are in one-to-one correspondence with the flow nodes. The characteristic value of the flow node data is brought into an echo state calculation formula, so that the state value of the initial flow node, namely the state value of the whole workflow, can be calculated. The method comprises the following steps:
wherein tan h is a fixed calculation formula, W in And W is res Is the variable parameter value, d (n) is the dimension of the tree, x (ch) i (n)) is the state value of the child node of the node, x (n) is the state value of the node, and n is the flow node n. When n=0, x (0) is the state value of the initial flow node.
S104: and determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree.
After passing through step S103, the state values x of the initial flow nodes in the first workflow structure tree are calculated 1 (0) And a state value x of an initial flow node in the second workflow structure tree 2 (0). The distance between the first workflow and the second workflow can then be determined.
In the embodiment of the present application, step S104 is specifically to determine, according to a euclidean distance calculation formula, a target distance between the first workflow and the second workflow according to a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree.
The Euclidean distance calculation formula is as follows:
d is distance, x 1 (n) is the state value of the flow node n in the first workflow tree structure, x 2 (n) is a state value of a flow node n in the second workflow tree structure.
By setting the state value x of the initial flow node in the first workflow structure tree 1 (0) And a state value x of an initial flow node in the second workflow structure tree 2 (0) And substituting the Euclidean distance calculation formula to determine the distance between the two initial nodes, namely the distance between the first workflow and the second workflow.
Of course, the distance between the other two flow nodes can also be calculated by the euclidean distance calculation formula. In the embodiment of the application, the distance between all corresponding flow nodes in the first workflow structure tree and the second workflow structure tree, such as the distance between the flow nodes 1 in the two workflow structure trees, namely x, can be calculated 1 (1) And x 2 (1) Substituting the Euclidean distance calculation formula.
The embodiment of the application provides some specific implementation manners of the workflow distance measuring method, and based on the specific implementation manners, the application also provides a corresponding device. The apparatus provided by the embodiment of the present application will be described in terms of functional modularization.
Referring to the schematic structure of the workflow distance measurement apparatus 600 shown in fig. 6, the apparatus 600 includes an acquisition module 610, a conversion module 620, a calculation module 630, and a measurement module 640.
An acquiring module 610, configured to acquire a first workflow and a second workflow;
the conversion module 620 is configured to convert the first workflow and the second workflow into tree structures, respectively, to obtain a first workflow structure tree and a second workflow structure tree;
a calculation module 630, configured to sequentially calculate the first workflow structure tree and the second workflow structure tree by using an echo state network, so as to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree;
and the measurement module 640 is configured to determine a distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree.
The embodiment of the application provides a measuring device for workflow distance. Firstly, a first workflow and a second workflow are acquired; then, converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree; sequentially calculating the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree; and finally, determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree. In this way, the workflow is displayed in the form of a tree structure, the structural characteristics of the workflow are met, and the thought based on a model space and the processing method of the echo state network are used, so that the workflow is instantiated in the model space, and the purpose of distance measurement is achieved.
In the embodiment of the present application, the conversion module 620 is specifically configured to:
determining the connection sequence between each flow node in the workflow;
deleting reverse connection among the flow nodes, and deleting the end flow nodes;
when two process nodes point to the same target process node at the same time, copying the target process node to serve as child nodes of the two process nodes respectively;
and taking the flow nodes and the connection sequence among the flow nodes as a workflow structure tree.
In an embodiment of the present application, the computing module 630 is specifically configured to:
defining flow node data characteristic values for each flow node in the workflow structure tree;
and calculating the state value of the initial flow node based on an echo state calculation formula by utilizing the flow node data characteristic value.
In the embodiment of the present application, the metric module 640 is specifically configured to:
and determining a target distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree by using a Euclidean distance calculation formula.
The device comprises a memory and a processor, wherein the memory is used for storing instructions or codes, and the processor is used for executing the instructions or codes to enable the device to execute the method for measuring the workflow distance according to any embodiment of the application.
The computer storage medium stores code, and when the code is executed, the device running the code realizes the method for measuring the distance of the workflow according to any embodiment of the application.
In the description of the embodiments of the present application, unless otherwise indicated, "/" means or, for example, a/B may represent a or B; "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, in the description of the embodiments of the present application, "plurality" means two or more than two.
The "first" and "second" in the names of "first", "second" (where present) and the like in the embodiments of the present application are used for name identification only, and do not represent the first and second in sequence.
From the above description of embodiments, it will be apparent to those skilled in the art that all or part of the steps of the above described example methods may be implemented in software plus general hardware platforms. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a storage medium, such as a read-only memory (ROM)/RAM, a magnetic disk, an optical disk, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network communication device such as a router) to perform the method according to the embodiments or some parts of the embodiments of the present application.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. 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 wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present application may be written in any combination of 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).
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present application without undue burden.
The foregoing description of the exemplary embodiments of the application is merely illustrative of the application and is not intended to limit the scope of the application.
Claims (10)
1. A method of measuring workflow distance, comprising:
acquiring a first workflow and a second workflow;
converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree;
sequentially calculating the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree;
and determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree.
2. The method of claim 1, wherein converting the workflow into a tree structure comprises:
determining the connection sequence between each flow node in the workflow;
deleting reverse connection among the flow nodes, and deleting the end flow nodes;
when two process nodes point to the same target process node at the same time, copying the target process node to serve as child nodes of the two process nodes respectively;
and taking the flow nodes and the connection sequence among the flow nodes as a workflow structure tree.
3. The method of claim 1, wherein the computing the workflow structure tree using the echo state network to obtain the state value of the initial flow node in the workflow structure tree comprises:
defining flow node data characteristic values for each flow node in the workflow structure tree;
and calculating the state value of the initial flow node based on an echo state calculation formula by utilizing the flow node data characteristic value.
4. The method of claim 1, wherein determining the distance between the first workflow and the second workflow based on the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree comprises:
and determining a target distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree by using a Euclidean distance calculation formula.
5. A workflow distance measurement apparatus, comprising:
the acquisition module is used for acquiring the first workflow and the second workflow;
the conversion module is used for converting the first workflow and the second workflow into tree structures respectively to obtain a first workflow structure tree and a second workflow structure tree;
the computing module is used for sequentially computing the first workflow structure tree and the second workflow structure tree by using an echo state network to obtain a state value of an initial flow node in the first workflow structure tree and a state value of an initial flow node in the second workflow structure tree;
and the measurement module is used for determining the distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree.
6. The apparatus of claim 5, wherein the conversion module is specifically configured to:
determining the connection sequence between each flow node in the workflow;
deleting reverse connection among the flow nodes, and deleting the end flow nodes;
when two process nodes point to the same target process node at the same time, copying the target process node to serve as child nodes of the two process nodes respectively;
and taking the flow nodes and the connection sequence among the flow nodes as a workflow structure tree.
7. The apparatus of claim 5, wherein the computing module is specifically configured to:
defining flow node data characteristic values for each flow node in the workflow structure tree;
and calculating the state value of the initial flow node based on an echo state calculation formula by utilizing the flow node data characteristic value.
8. The apparatus of claim 5, wherein the metric module is specifically configured to:
and determining a target distance between the first workflow and the second workflow according to the state value of the initial flow node in the first workflow structure tree and the state value of the initial flow node in the second workflow structure tree by using a Euclidean distance calculation formula.
9. A computer device, comprising: memory, a processor, and a computer program stored on the memory and executable on the processor, which processor, when executing the computer program, implements the method of measuring workflow distance according to any of claims 1-4.
10. A computer storage medium having instructions stored therein which, when run on a terminal device, cause the terminal device to perform the method of measuring workflow distance according to any of claims 1-4.
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