CN117171398B - Method, device and equipment for constructing service tree of industrial Internet platform - Google Patents
Method, device and equipment for constructing service tree of industrial Internet platform Download PDFInfo
- Publication number
- CN117171398B CN117171398B CN202311442690.1A CN202311442690A CN117171398B CN 117171398 B CN117171398 B CN 117171398B CN 202311442690 A CN202311442690 A CN 202311442690A CN 117171398 B CN117171398 B CN 117171398B
- Authority
- CN
- China
- Prior art keywords
- service
- service instance
- basic
- total number
- instance sets
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 235000010425 Sorbus domestica Nutrition 0.000 title claims abstract description 69
- 240000005332 Sorbus domestica Species 0.000 title claims abstract description 69
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000010586 diagram Methods 0.000 claims abstract description 55
- 238000010276 construction Methods 0.000 claims description 36
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 7
- 238000003860 storage Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 description 11
- 238000005457 optimization Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000009411 base construction Methods 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000019771 cognition Effects 0.000 description 1
- 230000001149 cognitive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a method, a device and equipment for constructing an industrial Internet platform service tree. The method for constructing the service tree of the industrial Internet platform comprises the following steps: calculating the correlation between any two services in the comprehensive service instance set in a service knowledge base based on a pre-constructed service knowledge base of a specified field of a specified industry; constructing a service relation diagram by taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as an edge and taking the magnitude of the correlation degree as the weight of the edge; constructing a maximum weight spanning tree of the service relation diagram by taking the designated service in the service relation diagram as a root node; and setting the undirected edge in the maximum weight spanning tree as a directed edge according to the service hierarchy direction to obtain a service tree corresponding to the service knowledge base. The method, the device and the equipment for constructing the service tree of the industrial Internet platform can automatically construct the service tree.
Description
Technical Field
The present application relates to the technical field of industrial internet, and in particular, to a method, an apparatus, and a device for building an industrial internet platform service tree.
Background
With the advent of the 5G age, networking has been in progress in various industries, particularly manufacturing involving multiple fields. In this context, the industry internet platform has been rapidly developed in recent years as a service-oriented advanced manufacturing model combining the traditional manufacturing industry with internet technology. Among them, the service package is one of the key technologies of the cloud-based manufacturing mode, including the release, registration, etc. of services, and is the key tie connecting the manufacturing industry with the internet.
In order to achieve the aim, the concept of an industrial Internet platform service tree is provided, wherein the concept is that on the basis of service analysis in the whole industrial chain of a product, service structure standards of multiple stages, multiple granularity and multiple dimensions of the product are formulated to determine service contents, service information, service structures, correlation relations and correlation rules of related industrial service activities of a typical product full life cycle. The service tree is used as a service structure standard in an industrial Internet platform system, and provides a standardized interface for service inquiry, release, matching and scheduling.
In the early stage of research, the construction of the service tree is in the service modeling stage, and on the basis of the model, the construction is performed manually by combining industry knowledge. And for an industrial internet platform, the system is oriented to various industries and relates to the full life cycle process of the industries. The knowledge surface for constructors is too high, and the workload is large and the accuracy is difficult to quantify. Therefore, a method for building an industrial internet platform service tree is needed to solve the problem of automatic building of the industrial internet platform service tree.
Disclosure of Invention
In view of this, the present application provides a method, apparatus and device for building an industrial internet platform service tree, which are used to solve the problem of automatic building of the industrial internet platform service tree, so that manufacturing services related to multiple industries in a full life cycle can be orderly accessed into an industrial internet platform system, and provide interface and data structure support for subsequent service combination optimization.
Specifically, the application is realized by the following technical scheme:
the first aspect of the application provides a method for constructing an industrial internet platform service tree, which comprises the following steps:
calculating the correlation between any two services in the comprehensive service instance set in a service knowledge base based on a pre-constructed service knowledge base of a specified field of a specified industry; the service knowledge base comprises a plurality of basic service instance sets and a comprehensive service instance set, each basic service instance set comprises a plurality of services, and the comprehensive service instance set summarizes all the services contained in the plurality of basic service instance sets;
Constructing a service relation diagram by taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as an edge and taking the magnitude of the correlation degree as the weight of the edge;
constructing a maximum weight spanning tree of the service relation diagram by taking the designated service in the service relation diagram as a root node;
and setting the undirected edge in the maximum weight spanning tree as a directed edge according to the service hierarchy direction to obtain a service tree corresponding to the service knowledge base.
A second aspect of the present application provides an industrial internet platform service tree construction apparatus, the apparatus comprising: a calculation module and a construction module; wherein,
the computing module is used for computing the correlation degree between any two services in the comprehensive service instance set in the service knowledge base based on a service knowledge base of a specified field of a specified industry, which is constructed in advance; the service knowledge base comprises a plurality of basic service instance sets and a comprehensive service instance set, each basic service instance set comprises a plurality of services, and the comprehensive service instance set summarizes all the services contained in the plurality of basic service instance sets;
The construction module is used for constructing a service relation diagram by taking each service in the service knowledge base as a node, taking the correlation between two services as an edge and taking the magnitude of the correlation as the weight of the edge;
the construction module is further used for constructing a maximum weight spanning tree of the service relation diagram by taking the designated service in the service relation diagram as a root node;
and the construction module is also used for setting the undirected edge in the maximum weight spanning tree as a directed edge according to the service hierarchy direction to obtain the service tree corresponding to the service knowledge base.
A third aspect of the present application provides an industrial internet platform service tree construction device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the methods provided in the first aspect of the present application when the program is executed.
A fourth aspect of the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the methods provided in the first aspect of the present application.
According to the industrial Internet platform service tree construction method, device and equipment, based on a service knowledge base in a specified field of a pre-constructed specified industry, a service relation diagram is constructed by calculating the correlation degree between any two services in a comprehensive service instance set in the service knowledge base, taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as edges and the size of the correlation degree as the weight of the edges, and further taking the specified service in the service relation diagram as a root node, the maximum weight generation tree of the service relation diagram is constructed, so that the undirected edges in the maximum weight generation tree are set as directed edges according to the service hierarchy direction, and the service tree corresponding to the service knowledge base is obtained. In this way, the correlation degree between any two services can be calculated based on a pre-constructed service knowledge base, a service relation diagram is constructed by taking each service in the comprehensive service instance set as a node, the correlation degree between two services as an edge, and the weight of the correlation degree between two services as an edge, further, a maximum weight spanning tree of the service relation diagram is constructed by taking a designated service in the service relation diagram as a root node, and the undirected edge in the maximum weight spanning tree is set as a directed edge according to the service hierarchy direction, so that a service tree corresponding to the service knowledge base is obtained, and an industrial Internet platform service tree can be automatically constructed, so that manufacturing services related to a plurality of industries in a full life cycle can be orderly accessed into an industrial Internet platform system, and interfaces and data structure support are provided for subsequent service combination optimization.
Drawings
FIG. 1 is a flowchart of a first embodiment of a method for building an industrial Internet platform service tree provided in the present application;
FIG. 2 is a schematic diagram of a service relationship diagram according to an exemplary embodiment of the present application;
FIG. 3 is a constructed service tree according to an exemplary embodiment of the present application;
FIG. 4 is a flowchart of a second embodiment of a method for building an industrial Internet platform service tree provided in the present application;
FIG. 5 is a hardware block diagram of an industrial Internet platform service tree construction device where the industrial Internet platform service tree construction device provided in the present application is located;
fig. 6 is a block diagram of an embodiment of an industrial internet platform service tree construction device provided in the present application.
Detailed Description
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 application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first message may also be referred to as a second message, and similarly, a second message may also be referred to as a first message, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
The application provides a method, a device and equipment for constructing an industrial Internet platform service tree, which are used for solving the problem of automatic construction of the industrial Internet platform service tree, so that manufacturing services related to the full life cycle of a plurality of industries can be orderly accessed into an industrial Internet platform system, and interfaces and data structure support are provided for subsequent service combination optimization.
According to the industrial Internet platform service tree construction method, device and equipment, based on a service knowledge base in a specified field of a pre-constructed specified industry, a service relation diagram is constructed by calculating the correlation degree between any two services in a comprehensive service instance set in the service knowledge base, taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as edges and the size of the correlation degree as the weight of the edges, and further taking the specified service in the service relation diagram as a root node, the maximum weight generation tree of the service relation diagram is constructed, so that the undirected edges in the maximum weight generation tree are set as directed edges according to the service hierarchy direction, and the service tree corresponding to the service knowledge base is obtained. In this way, the correlation degree between any two services can be calculated based on a pre-constructed service knowledge base, a service relation diagram is constructed by taking each service in the comprehensive service instance set as a node, the correlation degree between two services as an edge, and the weight of the correlation degree between two services as an edge, further, a maximum weight spanning tree of the service relation diagram is constructed by taking a designated service in the service relation diagram as a root node, and the undirected edge in the maximum weight spanning tree is set as a directed edge according to the service hierarchy direction, so that a service tree corresponding to the service knowledge base is obtained, and an industrial Internet platform service tree can be automatically constructed, so that manufacturing services related to a plurality of industries in a full life cycle can be orderly accessed into an industrial Internet platform system, and interfaces and data structure support are provided for subsequent service combination optimization.
Specific examples are given below to describe the technical solutions of the present application in detail.
Fig. 1 is a flowchart of an embodiment of a method for constructing an industrial internet platform service tree provided in the present application. Referring to fig. 1, the method provided in this embodiment includes:
s101, calculating the correlation degree between any two services in a comprehensive service instance set in a service knowledge base based on a service knowledge base of a specified field of a pre-constructed specified industry; the service knowledge base comprises a plurality of basic service instance sets and a comprehensive service instance set, wherein each basic service instance set comprises a plurality of services, and the comprehensive service instance set summarizes the services contained in the basic service instance sets.
Specifically, the designated industry is selected according to actual needs, and in this embodiment, the designated industry is not limited. For example, in one embodiment, the designated industry is the bicycle industry. The designated area is selected according to actual needs, and in this embodiment, the designated area is not limited. For example, in one embodiment, the designated area is the area of bicycle accessories.
Further, the service repository is a database for storing and managing service-related information, in which names of services, attribute information, relationships between services, and the like can be recorded.
It should be noted that, in order to make the service tree have both the expertise and the universality, in constructing the service knowledge base, the following knowledge and data should be combined to construct the service knowledge base:
(1) Industry expertise of the specified industry; it should be noted that, industry expertise may include industry standards, technical documents, and the like, which may be used as important guiding basis for service knowledge base construction. Through the industry expertise of the appointed industry, the frame of the service, the attribute of the service and the correlation between the services can be defined, so that the professionality and the accuracy of the constructed service tree are ensured.
(2) Industry usage data; the industry usage data may be business data, transaction data, etc. in the industry, and adding such data may ensure the universality of the service framework.
(3) Industry related data from the Internet, such terms used for a plurality of times such as short for service and the like, or service structures are mainly considered, and meanwhile, the inertia cognition of service users outside the industry to the service is considered.
By summarizing the three types of knowledge, the service expertise is ensured, and the cognitive habits of the service provider and the user are considered.
Specifically, the service repository includes a plurality of sets of base service instances and a set of comprehensive service instances. Wherein the plurality of basic service instance sets may be represented as s= { S 1 ,S 2 ,...S n }，S i ={x a ,x b ,...x t And each service included in the i-th basic service instance set, where i is equal to 1 to n. The integrated service instance set may be represented as d= { x 1 ,x 2 ,...x m }, where { x }, x 1 ,x 2 ,...x m And each service included in the plurality of underlying service instance sets. The integrated service instance set summarizes each service contained in the plurality of basic service instance sets. In other words, the integrated service instance set is a service instance set obtained by integrating services included in the plurality of basic service instance sets.
Specifically, a set of base service instances includes multiple services, for example, in one possible implementation, a set of base service instances may be represented as: the basic service instance set includes 13 services. In connection with the above example, for example, in one embodiment, the constructed service knowledge base includes n basic service instance sets, where the n basic service instance sets are shown in table 1:
TABLE 1 multiple underlying service instance sets in a service repository
As can be seen from the foregoing description, the integrated service instance set aggregates the services contained in the plurality of basic service instance sets. In the example shown in table 1, the integrated service instance set includes 13 services, where the 13 services are summary results of the services included in the n basic service instance sets, and the 13 services are respectively a mountain bike accessory service, a bicycle equipment service, a vehicle lamp service, a stopwatch service, a bicycle lock service, an inflator service, a kettle service, a bell service, a mud guard service, a cushion service, a pedal service, and a foot support service, that is, at this time, the services included in the integrated service instance set are as shown in table 2:
table 2 comprehensive service instance set
For example, in the example shown in table 2, the correlation between any two services in the calculated integrated service instance set is as shown in table 3:
table 3 correlation between any two services in a comprehensive service instance set
Wherein, in the example shown in Table 3, R ij Representing the correlation between service i and service j in the integrated service instance set. The specific implementation process and implementation principle related to calculating the correlation degree between any two services in the comprehensive service instance set in the service knowledge base will be described in the following embodiments, which are not repeated herein.
S102, constructing a service relation diagram by taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as an edge and taking the magnitude of the correlation degree as the weight of the edge.
Specifically, the constructed service relation graph is an undirected graph, wherein a node represents each service in the comprehensive service instance set, an edge represents the correlation degree between two services, and the weight of the edge represents the magnitude of the correlation degree between two services connected by the edge.
In specific implementation, firstly, all nodes in a service relation diagram are determined according to the existing comprehensive service instance set (namely, each service in the comprehensive service instance set is used as a node), then, for any two nodes, the correlation degree between the two nodes is used as an edge, and the magnitude of the correlation degree between the two nodes is used as the weight of the edge to be added into the service relation diagram.
For example, in one possible implementation of the present application, the integrated service instance set contains 5 services, which 5 services are denoted as x, respectively 1 、x 2 、x 3 、x 4 、x 5 And is calculated to obtain x 1 And x 2 The correlation degree between is r 12 ，x 1 And x 3 The correlation degree between is r 13 ，x 1 And x 4 The correlation degree between is r 14 ，x 1 And x 5 The correlation degree between is r 15 ，x 2 And x 3 The correlation degree between is r 23 ，x 2 And x 4 The correlation degree between is r 24 ，x 2 And x 5 The correlation degree between is r 25 ，x 3 And x 4 The correlation degree between is r 34 ，x 3 And x 5 The correlation degree between is r 35 ，x 4 And x 5 The correlation degree between is r 45 . At this time, in this step, the constructed service relationship diagram is shown in fig. 2 (fig. 2 is a schematic diagram of a service relationship diagram according to an exemplary embodiment of the present application). Referring to fig. 2, the service relationship diagram includes 5 nodes, each node corresponds to a service, an edge exists between two services, and the weight of the edge is two connected with the edgeCorrelation between individual services.
S103, constructing a maximum weight spanning tree of the service relation diagram by taking the designated service in the service relation diagram as a root node.
Specifically, the specified service is set according to actual needs, and in this embodiment, it is not limited. For example, in one possible implementation, the specified service is the most frequently occurring service of the plurality of underlying service instance sets.
Specifically, a maximum weight spanning tree algorithm may be employed to construct a maximum weight spanning tree for the service relationship graph. In the specific implementation, one edge with the largest weight is selected from all edges containing the root node as a starting edge, and then in each step, one edge with the largest weight is always selected from unselected edges which do not form a loop with the selected edge. If two or more sides are the sides with the greatest weight, one side is selected.
S104, setting the undirected edge in the maximum weight spanning tree as a directed edge according to the service hierarchy direction, and obtaining a service tree corresponding to the service knowledge base.
Specifically, the service level direction is set according to actual needs, which is not limited in this embodiment, for example, in an embodiment, the service level direction is from the root node to the node connected to the root node.
For example, in connection with the example of table 3, in one embodiment, fig. 3 is a constructed service tree as illustrated in an exemplary embodiment of the present application. Referring to fig. 3, the service tree includes a root node that is a mountain bike accessory, further, includes a cascaded two-layer hierarchical structure below the root node, the first layer hierarchical structure including a bicycle accessory and bicycle equipment, further, under the bicycle accessory, including a seat cushion, pedals, and a foot rest. Under bicycle equipment, including lamps, stopwatches, locks, inflators, kettles, bells and mud flaps.
According to the industrial Internet platform service tree construction method, based on a service knowledge base of a specified field of a pre-constructed specified industry, a service relation diagram is constructed by calculating the correlation degree between any two services in a comprehensive service instance set in the service knowledge base, taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as edges and the size of the correlation degree as the weight of the edges, and further, a maximum weight generation tree of the service relation diagram is constructed by taking the specified service in the service relation diagram as a root node, so that an undirected edge in the maximum weight generation tree is set as a directed edge according to a service hierarchy direction, and the service tree corresponding to the service knowledge base is obtained. In this way, the correlation degree between any two services can be calculated based on a pre-constructed service knowledge base, a service relation diagram is constructed by taking each service in the comprehensive service instance set as a node, the correlation degree between two services as an edge, and the weight of the correlation degree between two services as an edge, further, a maximum weight spanning tree of the service relation diagram is constructed by taking a designated service in the service relation diagram as a root node, and the undirected edge in the maximum weight spanning tree is set as a directed edge according to the service hierarchy direction, so that a service tree corresponding to the service knowledge base is obtained, and an industrial Internet platform service tree can be automatically constructed, so that manufacturing services related to a plurality of industries in a full life cycle can be orderly accessed into an industrial Internet platform system, and interfaces and data structure support are provided for subsequent service combination optimization.
Fig. 4 is a flowchart of a second embodiment of a method for constructing an industrial internet platform service tree provided in the present application. Referring to fig. 4, in the method provided in this embodiment, on the basis of the foregoing embodiment, the calculating a correlation between any two services in the service knowledge base includes:
s401, counting the total number of services contained in the plurality of basic service instance sets.
In connection with the above example, the plurality of basic service instance sets may be represented as s= { S 1 ,S 2 ,...S n }，S i ={x a ,x b ,...x t And each service included in the i-th basic service instance set, where i is equal to 1 to n. The integrated service instance set may be represented as d= { x 1 ,x 2 ,...x m }，Wherein { x 1 ,x 2 ,...x m And each service included in the plurality of underlying service instance sets.
In this step, specifically, the total number of services included in the plurality of basic service instance sets may be counted according to the following formula:,
wherein Q is 0 Representing a total number of services contained by the plurality of underlying service instance sets; n represents the number of the plurality of underlying service instance sets; s is S i Representing an i-th set of basic service instances, i being equal to 1 to n; s i The i indicates the number of services contained in the i-th set of basic service instances.
S402, counting first total times of occurrence of the target service in the plurality of basic service instance sets aiming at each target service in the comprehensive service instance set.
Specifically, the target service refers to any one of the services in the integrated service instance set. In particular, for a target service, the first total number of occurrences of the target service in the plurality of basic service instance sets may be counted according to the following formula:
,
wherein,representing a first total number of occurrences of a jth target service in the plurality of underlying service instance sets, j being equal to 1 through m; n represents the number of basic service instance sets; x is x j Representing the j-th target service in the integrated service instance set, j being equal to 1 to m; s is S i Representing the ith basic service instance set, +.>Representing the number of times the jth target service appears in the ith set of basic service instances.
S403, calculating the probability of the target service in the plurality of basic service instance sets according to the first total number of the target service in the plurality of basic service instance sets and the total number for each target service.
In particular implementations, for each target service, a ratio of a first total number of occurrences of the target service in a plurality of underlying service instance sets to the total number may be determined as a probability of occurrence of the target service in the plurality of underlying service instance sets.
In other words, for each target service, the probability of that target service occurring in the plurality of underlying service instance sets may be calculated according to the following formula:
,
wherein P (x) A ) Representing a target service x A Probability of occurrence in the plurality of underlying service instance sets;representing a target service x A A first total number of occurrences in the plurality of underlying service instance sets; q (Q) 0 Representing a total number of services contained by the plurality of underlying service instance sets; n represents the number of the plurality of underlying service instance sets; x is x A Representing any one of the target services in the integrated service instance set; s is S i Representing an ith set of basic service instances; />Representing the number of times the A-th target service appears in the i-th set of basic service instances, A being equal to 1 to m; s i I denotes the number of services contained in the i-th set of basic service instances, i being equal to 1 to n.
S404, calculating a second total number of times that the first service and the second service simultaneously appear in the same basic service instance set aiming at the first service and the second service in the comprehensive service instance set.
In particular, the second total number of times that the first service and the second service are simultaneously present in the same set of base service instances may be calculated according to the following formula:
,
Wherein,representing the first service x A And the second service x B A second total number of simultaneous occurrences in the same set of base service instances; n represents the number of the plurality of underlying service instance sets; x is x A Representing the first service; x is x B Representing the second service, the first service and the second service being any two services in the integrated service instance set; s is S i Representing an ith set of basic service instances; />Representing a first service x A And a second service x B And the number of times that it appears in the ith set of basic service instances.
S405, calculating the probability that the first service and the second service are simultaneously appeared in the plurality of basic service instance sets according to the second total times, the first total times of the first service in the plurality of basic service instance sets and the first total times of the second service in the plurality of basic service instance sets.
Specifically, the implementation process of this step may include:
(1) And calculating the square root of the product of the first total times of the first service in the plurality of basic service instance sets and the first total times of the second service in the plurality of basic service instance sets to obtain a first calculation result.
Specifically, the first calculation result may be obtained according to the following formula:
,
wherein C represents the first calculation result;representing a first total number of occurrences of the first service in the plurality of underlying service instance sets; />Representing a first total number of occurrences of the second service in the plurality of underlying service instance sets; n represents the number of the plurality of underlying service instance sets; x is x A Representing the first service; x is x B Representing the second service; s is S i Representing an ith set of basic service instances; />Representing the number of times the A-th target service appears in the i-th set of basic service instances; />Representing the number of times the B-th target service appears in the i-th set of basic service instances.
(2) A ratio of the second total number of times to the first calculation result is determined as a probability that the first service and the second service occur simultaneously in the plurality of underlying service instance sets.
Specifically, the probability that the first service and the second service occur in the plurality of basic service instance sets at the same time may be calculated according to the following formula:
,
wherein P (x) A ,x B ) Representing the first service x A And the second service x B The probability of simultaneous occurrence in the plurality of underlying service instance sets; Representing the first service x A And the second service x B A second total number of simultaneous occurrences in the same set of base service instances; c represents the first calculation result; n represents the number of the plurality of underlying service instance sets; x is x A Representing the first service; x is x B Representing the second service; s is S i Representing an ith set of basic service instances;representing the number of times the A-th target service and the B-th target service occur simultaneously in the i-th basic service example set; />Representing the number of times the A-th target service appears in the i-th set of basic service instances; />Representing the number of times the B-th target service appears in the i-th set of basic service instances.
S406, calculating the correlation degree between the first service and the second service according to the probability of the first service in the plurality of basic service instance sets and the probability of the second service in the plurality of basic service instance sets.
Specifically, calculating the correlation between the first service and the second service according to a first formula; wherein, the first formula is:
,
Wherein R (x) A ,x B ) Representing the first service x A And the second service x B Correlation between the two; p (x) A ,x B ) Representing the first service x A And the second service x B The probability of simultaneous occurrence in the plurality of underlying service instance sets; P(x A ) Representing the first service x A Probability of occurrence in the plurality of underlying service instance sets; p (x) B ) Representing the second service x B Probability of occurrence in the plurality of underlying service instance sets; x is x A Representing the first service; x is x B Representing the second service; d represents the integrated service instance set.
According to the industrial Internet platform service tree construction method, total quantity of services contained in the multiple basic service instance sets is counted, first total times of occurrence of the target service in the multiple basic service instance sets are counted for each target service in the comprehensive service instance set, then according to the first total times of occurrence of the target service in the multiple basic service instance sets and the total quantity, probability of occurrence of the target service in the multiple basic service instance sets is calculated according to the first total times of occurrence of the target service in the multiple basic service instance sets and the total times, and according to first service and second service in the comprehensive service instance sets, second total times of occurrence of the first service and the second service in the same basic service instance set at the same time are calculated, and accordingly probability of occurrence of the first service and the second service in the multiple basic service instance sets is calculated according to the second total times, first times of occurrence of the first service in the multiple basic service instance sets and first total times of occurrence of the second service in the multiple basic service instance sets and probability of occurrence of the second service in the multiple basic service instance sets. In this way, the correlation degree between any two services in the service knowledge base can be calculated through a plurality of formulas, and support is provided for the subsequent construction of the service relation diagram.
Corresponding to the embodiment of the method for constructing the service tree of the industrial Internet platform, the application also provides an embodiment of the device for constructing the service tree of the industrial Internet platform.
The embodiment of the industrial Internet platform service tree construction device can be applied to industrial Internet platform service tree construction equipment. The apparatus embodiments may be implemented by software, or may be implemented by hardware or a combination of hardware and software. Taking software implementation as an example, the device in a logic sense is formed by reading corresponding computer program instructions in a nonvolatile memory into a memory through a processor of industrial internet platform service tree construction equipment where the device is located for operation. In terms of hardware, as shown in fig. 5, a hardware structure diagram of an industrial internet platform service tree construction device where the industrial internet platform service tree construction device provided in the present application is shown, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 5, where the industrial internet platform service tree construction device where the device is shown in the embodiment is generally according to the actual function of the industrial internet platform service tree construction device, other hardware may also be included, which is not described herein again.
Fig. 6 is a block diagram of an embodiment of an industrial internet platform service tree construction device provided in the present application. Referring to fig. 6, the apparatus provided in this embodiment includes: a calculation module 610 and a construction module 620; wherein,
the calculating module 610 is configured to calculate, based on a service knowledge base of a specified field of a specified industry, a correlation between any two services in the service knowledge base; the service knowledge base comprises a plurality of basic service instance sets and a comprehensive service instance set, each basic service instance set comprises a plurality of services, and the comprehensive service instance set summarizes all the services contained in the plurality of basic service instance sets;
the building module 620 is configured to build a service relationship graph with each service in the service knowledge base as a node, with a correlation between two services as an edge, and with a magnitude of the correlation as a weight of the edge;
the building module 620 is further configured to build a maximum weight spanning tree of the service relationship graph with a specified service in the service relationship graph as a root node;
the construction module 620 is further configured to set, according to a service hierarchy direction, an undirected edge in the maximum weight spanning tree as a directed edge, and obtain a service tree corresponding to the service knowledge base.
The device provided in this embodiment may be used to implement the technical method of the method embodiment shown in fig. 1, and its implementation principle and technical effects are similar, and will not be described here again.
According to the industrial Internet platform service tree construction device, based on the service knowledge base of the appointed field of the appointed industry constructed in advance, the service relation diagram is constructed by calculating the correlation degree between any two services in the comprehensive service instance set in the service knowledge base, taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as edges and taking the magnitude of the correlation degree as the weight of the edges, and further, the appointed service in the service relation diagram is taken as a root node, the maximum weight generation tree of the service relation diagram is constructed, so that the undirected edge in the maximum weight generation tree is set as a directed edge according to the service hierarchy direction, and the service tree corresponding to the service knowledge base is obtained. In this way, the correlation degree between any two services can be calculated based on a pre-constructed service knowledge base, a service relation diagram is constructed by taking each service in the comprehensive service instance set as a node, the correlation degree between two services as an edge, and the weight of the correlation degree between two services as an edge, further, a maximum weight spanning tree of the service relation diagram is constructed by taking a designated service in the service relation diagram as a root node, and the undirected edge in the maximum weight spanning tree is set as a directed edge according to the service hierarchy direction, so that a service tree corresponding to the service knowledge base is obtained, and an industrial Internet platform service tree can be automatically constructed, so that manufacturing services related to a plurality of industries in a full life cycle can be orderly accessed into an industrial Internet platform system, and interfaces and data structure support are provided for subsequent service combination optimization.
Optionally, the calculating module 610 is specifically configured to count the total number of services included in the plurality of basic service instance sets;
the computing module 610 is further specifically configured to, for each target service in the integrated service instance set, count a first total number of occurrences of the target service in the plurality of basic service instance sets;
the calculating module 610 is further specifically configured to calculate, for each of the target services, a probability that the target service appears in the plurality of basic service instance sets according to a first total number of occurrences of the target service in the plurality of basic service instance sets and the total number;
the calculating module 610 is further specifically configured to calculate, for a first service and a second service in the integrated service instance set, a second total number of times that the first service and the second service are simultaneously present in the same basic service instance set;
the calculating module 610 is further specifically configured to calculate a probability that the first service and the second service occur in the plurality of basic service instance sets at the same time according to the second total number of times, the first total number of times the first service occurs in the plurality of basic service instance sets, and the first total number of times the second service occurs in the plurality of basic service instance sets;
The calculating module 610 is further specifically configured to calculate a correlation between the first service and the second service according to the probability that the first service appears in the plurality of basic service instance sets, the probability that the second service appears in the plurality of basic service instance sets, and the probability that the first service and the second service appear in the plurality of basic service instance sets at the same time.
Optionally, the calculating module 610 is specifically configured to determine a ratio of the first total number to the total number as a probability that the target service occurs in the plurality of basic service instance sets.
Optionally, the calculating module 610 is specifically configured to calculate a square root of a product of a first total number of times the first service appears in the plurality of basic service instance sets and a first total number of times the second service appears in the plurality of basic service instance sets, to obtain a first calculation result;
the calculating module 610 is further specifically configured to determine a ratio of the second total number of times to the first calculation result as a probability that the first service and the second service occur in the plurality of basic service instance sets simultaneously.
Optionally, the calculating module 610 is specifically configured to calculate a correlation between the first service and the second service according to a first formula; wherein, the first formula is:
,
wherein R (x) A ,x B ) Representing a correlation between the first service and the second service;
P(x A ,x B ) Representing a probability that the first service and the second service occur simultaneously in the plurality of underlying service instance sets;
P(x A ) Representing a probability of occurrence of the first service in the plurality of underlying service instance sets;
P(x B ) Representing a probability of occurrence of the second service in the plurality of underlying service instance sets;
x A representing the first service;
x B representing the second service;
d represents the integrated service instance set.
With continued reference to fig. 5, the present application further provides an industrial internet platform service tree construction device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of any of the methods provided in the first aspect of the present application when the program is executed.
Further, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of any of the methods provided in the first aspect of the present application.
The implementation process of the functions and roles of each unit in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.
For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present application. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing description of the preferred embodiments of the present invention is not intended to limit the invention to the precise form disclosed, and any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. An industrial internet platform service tree construction method, which is characterized by comprising the following steps:
Calculating the correlation between any two services in the comprehensive service instance set in a service knowledge base based on a pre-constructed service knowledge base of a specified field of a specified industry; the service knowledge base comprises a plurality of basic service instance sets and a comprehensive service instance set, each basic service instance set comprises a plurality of services, and the comprehensive service instance set summarizes all the services contained in the plurality of basic service instance sets;
constructing a service relation diagram by taking each service in the comprehensive service instance set as a node, taking the correlation degree between two services as an edge and taking the magnitude of the correlation degree as the weight of the edge;
constructing a maximum weight spanning tree of the service relation diagram by taking the designated service in the service relation diagram as a root node;
setting undirected edges in the maximum weight spanning tree as directed edges according to the service level direction to obtain a service tree corresponding to the service knowledge base;
the calculating the correlation degree between any two services in the service knowledge base comprises the following steps:
counting the total number of services contained in the plurality of basic service instance sets;
Counting a first total number of occurrences of the target service in the plurality of basic service instance sets for each target service in the comprehensive service instance set;
calculating, for each of the target services, a probability that the target service appears in the plurality of underlying service instance sets based on a first total number of occurrences of the target service in the plurality of underlying service instance sets and the total number;
calculating a second total number of times that the first service and the second service are simultaneously present in the same basic service instance set for the first service and the second service in the comprehensive service instance set;
calculating the probability that the first service and the second service are simultaneously appeared in the plurality of basic service instance sets according to the second total times, the first total times of the first service appearing in the plurality of basic service instance sets and the first total times of the second service appearing in the plurality of basic service instance sets;
and calculating the correlation between the first service and the second service according to the probability of the first service in the plurality of basic service instance sets, the probability of the second service in the plurality of basic service instance sets and the probability of the first service and the second service in the plurality of basic service instance sets simultaneously.
2. The method of claim 1, wherein the calculating the probability that the target service will occur in the plurality of basic service instance sets based on the first total number of occurrences of the target service in the plurality of basic service instance sets and the total number comprises:
a ratio of the first total number and the total number is determined as a probability that the target service appears in the plurality of underlying service instance sets.
3. The method of claim 1, wherein the calculating the probability that the first service and the second service occur simultaneously in the plurality of basic service instance sets based on the second total number of times, the first total number of times the first service occurs in the plurality of basic service instance sets, and the first total number of times the second service occurs in the plurality of basic service instance sets comprises:
calculating the square root of the product of the first total times of the first service in the plurality of basic service instance sets and the first total times of the second service in the plurality of basic service instance sets to obtain a first calculation result;
A ratio of the second total number of times to the first calculation result is determined as a probability that the first service and the second service occur simultaneously in the plurality of underlying service instance sets.
4. The method of claim 1, wherein the calculating the correlation between the first service and the second service based on the probability of the first service occurring in the plurality of basic service instance sets, the probability of the second service occurring in the plurality of basic service instance sets, and the probability of the first service and the second service occurring in the plurality of basic service instance sets simultaneously, comprises:
calculating the correlation between the first service and the second service according to a first formula; wherein, the first formula is:
,
wherein,representing a correlation between the first service and the second service;
representing a probability that the first service and the second service occur simultaneously in the plurality of underlying service instance sets;
representing a probability of occurrence of the first service in the plurality of underlying service instance sets;
representing a probability of occurrence of the second service in the plurality of underlying service instance sets;
Representing the first service;
representing the second service;
d represents the integrated service instance set.
5. An industrial internet platform service tree construction apparatus, the apparatus comprising: a calculation module and a construction module; wherein,
the computing module is used for computing the correlation degree between any two services in the comprehensive service instance set in the service knowledge base based on a service knowledge base of a specified field of a specified industry, which is constructed in advance; the service knowledge base comprises a plurality of basic service instance sets and a comprehensive service instance set, each basic service instance set comprises a plurality of services, and the comprehensive service instance set summarizes all the services contained in the plurality of basic service instance sets;
the construction module is used for constructing a service relation diagram by taking each service in the service knowledge base as a node, taking the correlation between two services as an edge and taking the magnitude of the correlation as the weight of the edge;
the construction module is further used for constructing a maximum weight spanning tree of the service relation diagram by taking the designated service in the service relation diagram as a root node;
The construction module is further configured to set an undirected edge in the maximum weight spanning tree as a directed edge according to a service level direction, so as to obtain a service tree corresponding to the service knowledge base;
the computing module is specifically configured to count total number of services contained in the plurality of basic service instance sets;
the computing module is specifically configured to count, for each target service in the integrated service instance set, a first total number of times that the target service appears in the plurality of basic service instance sets;
the computing module is specifically configured to, for each of the target services, compute a probability that the target service appears in the plurality of basic service instance sets according to a first total number of occurrences of the target service in the plurality of basic service instance sets and the total number;
the computing module is specifically configured to compute, for a first service and a second service in the integrated service instance set, a second total number of times that the first service and the second service simultaneously appear in the same basic service instance set;
the calculating module is specifically configured to calculate a probability that the first service and the second service occur in the plurality of basic service instance sets at the same time according to the second total number of times, the first total number of times that the first service occurs in the plurality of basic service instance sets, and the first total number of times that the second service occurs in the plurality of basic service instance sets;
The calculating module is specifically configured to calculate a correlation between the first service and the second service according to probabilities that the first service appears in the plurality of basic service instance sets, probabilities that the second service appears in the plurality of basic service instance sets, and probabilities that the first service and the second service appear in the plurality of basic service instance sets at the same time.
6. The apparatus according to claim 5, wherein the calculating module is configured to determine a ratio of the first total number and the total number as a probability that the target service appears in the plurality of underlying service instance sets.
7. The apparatus of claim 5, wherein the computing module is configured to compute a square root of a product of a first total number of times the first service occurs in the plurality of basic service instance sets and a first total number of times the second service occurs in the plurality of basic service instance sets to obtain a first computation result;
the calculating module is further specifically configured to determine a ratio of the second total number of times to the first calculation result as a probability that the first service and the second service occur in the plurality of basic service instance sets at the same time.
8. An industrial internet platform service tree construction device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1-4 when the program is executed by the processor.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311442690.1A CN117171398B (en) | 2023-11-01 | 2023-11-01 | Method, device and equipment for constructing service tree of industrial Internet platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311442690.1A CN117171398B (en) | 2023-11-01 | 2023-11-01 | Method, device and equipment for constructing service tree of industrial Internet platform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117171398A CN117171398A (en) | 2023-12-05 |
| CN117171398B true CN117171398B (en) | 2024-02-09 |
Family
ID=88937866
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311442690.1A Active CN117171398B (en) | 2023-11-01 | 2023-11-01 | Method, device and equipment for constructing service tree of industrial Internet platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117171398B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102521659A (en) * | 2011-11-26 | 2012-06-27 | 北京航空航天大学 | Method for judging incidence relation between services orienting to cloud manufacturing |
| CN108962384A (en) * | 2018-07-03 | 2018-12-07 | 科大讯飞股份有限公司 | A kind of result of decision determines method, apparatus, equipment and readable storage medium storing program for executing |
| CN109460479A (en) * | 2018-11-19 | 2019-03-12 | 广州合摩计算机科技有限公司 | A kind of prediction technique based on reason map, device and system |
| KR20190055023A (en) * | 2019-01-28 | 2019-05-22 | 스닙팟 주식회사 | Personalized topic network service method with tree structure of hashtag and system therefor |
| CN112883120A (en) * | 2019-11-29 | 2021-06-01 | 南京苏德创新科技有限公司 | Inter-service association relation judgment algorithm for realizing high sharing of manufacturing resources by utilizing information technology |
| CN113014674A (en) * | 2021-04-08 | 2021-06-22 | 北京百度网讯科技有限公司 | Method and device for drawing service dependency graph |
| CN114491435A (en) * | 2021-12-22 | 2022-05-13 | 山东浪潮工业互联网产业股份有限公司 | Safety access method and equipment based on industrial internet platform |
| US11347625B1 (en) * | 2020-10-19 | 2022-05-31 | Splunk Inc. | Rendering a service graph illustrate page provider dependencies at query time using exemplars |
-
2023
- 2023-11-01 CN CN202311442690.1A patent/CN117171398B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102521659A (en) * | 2011-11-26 | 2012-06-27 | 北京航空航天大学 | Method for judging incidence relation between services orienting to cloud manufacturing |
| CN108962384A (en) * | 2018-07-03 | 2018-12-07 | 科大讯飞股份有限公司 | A kind of result of decision determines method, apparatus, equipment and readable storage medium storing program for executing |
| CN109460479A (en) * | 2018-11-19 | 2019-03-12 | 广州合摩计算机科技有限公司 | A kind of prediction technique based on reason map, device and system |
| KR20190055023A (en) * | 2019-01-28 | 2019-05-22 | 스닙팟 주식회사 | Personalized topic network service method with tree structure of hashtag and system therefor |
| CN112883120A (en) * | 2019-11-29 | 2021-06-01 | 南京苏德创新科技有限公司 | Inter-service association relation judgment algorithm for realizing high sharing of manufacturing resources by utilizing information technology |
| US11347625B1 (en) * | 2020-10-19 | 2022-05-31 | Splunk Inc. | Rendering a service graph illustrate page provider dependencies at query time using exemplars |
| CN113014674A (en) * | 2021-04-08 | 2021-06-22 | 北京百度网讯科技有限公司 | Method and device for drawing service dependency graph |
| CN114491435A (en) * | 2021-12-22 | 2022-05-13 | 山东浪潮工业互联网产业股份有限公司 | Safety access method and equipment based on industrial internet platform |
Non-Patent Citations (2)
| Title |
|---|
| Service Deployment Strategies for Efficient Execution of Composite SaaS Applications on Cloud Platform;Kuo-Chan Huang et al;《Joural of Systems and Software》(第107期);第127-141页 * |
| 基于服务关系图的Web服务组合算法;袁玉倩 等;《计算机应用与软件》;第32卷(第6期);第30-33, 65页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117171398A (en) | 2023-12-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN100437589C (en) | Multidimensional expression data caching method and device in online analytical processing system | |
| CN102521411B (en) | Formula and formula data processing device and formula and formula data processing method | |
| CN107038262B (en) | A kind of Semantic Modeling Method based on data map, Information Atlas and knowledge mapping frame that association frequency calculates | |
| US7769762B2 (en) | Method and system for consolidating data type repositories | |
| US20080256121A1 (en) | Method and system for mapping multi-dimensional model to data warehouse schema | |
| CA2804441C (en) | Database performance analysis | |
| CN110909066B (en) | Streaming data processing method based on SparkSQL and RestAPI | |
| Schnaitter et al. | Evaluating rank joins with optimal cost | |
| CN107430611A (en) | Filter data lineage figure | |
| JP2013512517A (en) | Method, system, and computer program for unbalanced hierarchy compensation when generating an OLAP query from a report specification | |
| CN112434024B (en) | Relational database-oriented data dictionary generation method, device, equipment and medium | |
| CN113987105B (en) | Label perception graphics stream sketch construction method and application based on sliding window | |
| CN110175184A (en) | A kind of lower drill method, system and the electronic equipment of data dimension | |
| CN115374329A (en) | Method and system for managing enterprise business metadata and technical metadata | |
| CN115292344A (en) | Data dictionary construction method and device, electronic equipment and storage medium | |
| CN113468163B (en) | Multisource heterogeneous public security big data intelligent docking engine system | |
| CN117171398B (en) | Method, device and equipment for constructing service tree of industrial Internet platform | |
| CN103294791A (en) | Extensible markup language pattern matching method | |
| CN115061662B (en) | MBSE-based heterogeneous model integration method and system for interconnection platform | |
| Kanne et al. | A linear time algorithm for optimal tree sibling partitioning and approximation algorithms in natix | |
| CN101770627A (en) | Method and device for evaluating service relative trust | |
| CN108830030A (en) | Atom typing rule_ system and its atomic type matching process | |
| CN114490571A (en) | Modeling method, server and storage medium | |
| Halpin | Join constraints | |
| Pérez Morago | BDD algorithms to perform hard analysis operations on variability models |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |