CN116304091A - Construction and application method, device, equipment and medium of design selection type knowledge graph - Google Patents
Construction and application method, device, equipment and medium of design selection type knowledge graph Download PDFInfo
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Abstract
The embodiment of the invention discloses a construction and application method of a design selection type knowledge graph, which relates to the field of power distribution network design, and comprises the following steps: obtaining a design material to be analyzed; analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information; extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity; and constructing a design selection type knowledge graph according to all the target entities and the association relation among the target entities. According to the invention, the design type selection knowledge graph is constructed in a mode of analyzing the target entity from the design material, and based on the design type selection knowledge graph, a designer can effectively improve the efficiency of carrying out the design type selection work of the distribution network.
Description
Technical Field
The invention relates to the technical field of knowledge maps and the field of power distribution networks, in particular to a construction and application method, a device, equipment and a medium of a design selection type knowledge map.
Background
When a designer performs a network design selection, the materials used in any legend, the wiring relationships, the wiring schemes, and the wires used in each wiring scheme are generally configured according to the experience of the designer. For the designer who is not familiar with the design and selection of the distribution network, the design process of the distribution network is complicated and inefficient according to experience. For the distribution network design of large-scale distribution network projects, a great deal of time and energy are consumed for the distribution network design according to experience, and the working efficiency of designers cannot be guaranteed.
Therefore, an application scheme capable of effectively improving the efficiency of the distribution network design of the designer is needed.
Disclosure of Invention
In order to solve the above technical problems, embodiments of the present application provide a method, an apparatus, a device, and a medium for constructing and applying a design selection type knowledge graph, where the specific scheme is as follows:
in a first aspect, an embodiment of the present application provides a method for constructing a design selection type knowledge graph, including:
obtaining a design material to be analyzed;
analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information;
extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity;
and constructing a design selection type knowledge graph according to all the target entities and the association relation among the target entities.
According to a specific implementation manner of the embodiment of the present application, the extracting and constructing n target entities based on the design selection data includes:
and extracting and constructing n target entities based on the design selection data according to the knowledge representation mode of the attribute graph.
According to a specific implementation manner of the embodiments of the present application, the constructing a design selection knowledge graph according to all target entities and association relations between the target entities includes:
combining different types of target entities according to the association relation among the target entities to obtain m atlas patterns corresponding to m legend entities, wherein m is a positive integer;
and storing the triples corresponding to each pattern mode into a preset pattern database to generate the design selection type knowledge pattern.
According to a specific implementation manner of the embodiment of the present application, the preset map database is a Neo4j map database.
According to a specific implementation manner of the embodiments of the present application, after the design selection knowledge graph is constructed according to all the target entities and the association relationships between the target entities, the method further includes:
acquiring a newly added target entity;
updating the design selection type knowledge graph according to the type of the newly added legend entity;
if the newly added target entity is a newly added legend entity, a new pattern is constructed according to the newly added legend entity and the target entity related to the newly added legend entity, and triples corresponding to the pattern are stored in the preset map database so as to update the design selection type knowledge map;
if the newly added target entity is not the newly added legend entity, adding the newly added target entity into the corresponding pattern according to the type of the newly added target entity and the association relation with the corresponding pattern so as to update the design selection type knowledge pattern.
In a second aspect, an embodiment of the present application provides an application method for designing a model selection knowledge graph, including:
acquiring legend information to be queried and a query target;
analyzing the legend information to be queried to obtain a legend entity to be queried;
and matching target entities corresponding to the legend entities to be queried in a preset design selection type knowledge graph, and deriving output entities corresponding to the query targets, wherein the output entities are at least one of material group entities, overhead line relationship entities, overhead line entities, material entities and wire entities.
According to a specific implementation manner of the embodiments of the present application, the matching the target entity corresponding to the legend entity to be queried in the preset design selection type knowledge graph, and deriving the output entity corresponding to the query target, includes:
acquiring a plurality of target entities corresponding to the legend entity to be queried, wherein each target entity comprises a historical use frequency attribute;
and sorting the target entities according to the historical use times attribute, and deriving the target entity with the largest historical use times as an output entity corresponding to the query target.
In a third aspect, an embodiment of the present application provides a device for constructing a design selection type knowledge graph, including:
the material acquisition module is used for acquiring the design material to be analyzed;
the material analysis module is used for analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information;
the entity construction module is used for extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity;
and the map construction module is used for constructing a design selection type knowledge map according to all target entities and the association relation among all target entities.
In a fourth aspect, an embodiment of the present application provides an application apparatus for designing a selection-type knowledge graph, including:
the query acquisition module is used for acquiring the legend information to be queried and the query target;
the query analysis module is used for analyzing the legend information to be queried to obtain a legend entity to be queried;
and the map query module is used for matching the target entity corresponding to the legend entity to be queried in a preset design selection type knowledge map, and deriving an output entity corresponding to the query target, wherein the output entity is at least one of a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity.
In a fifth aspect, an embodiment of the present application provides a computer device, where the computer device includes a processor and a memory, where the memory stores a computer program, and the computer program executes, when running on the processor, a method for constructing a design selection type knowledge graph according to any one of the first aspect and the implementation manner of the first aspect, and a method for applying the design selection type knowledge graph according to the second aspect.
In a sixth aspect, an embodiment of the present application provides a computer readable storage medium, where a computer program is stored, where the computer program executes, when running on a processor, a method for constructing a design selection type knowledge graph according to any one of the first aspect and the first embodiment and a method for applying the design selection type knowledge graph according to the second aspect.
The embodiment of the application provides a construction and application method of a design selection knowledge graph, which comprises the following steps: obtaining a design material to be analyzed; analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information; extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity; and constructing a design selection type knowledge graph according to all the target entities and the association relation among the target entities. According to the invention, firstly, the pattern mode design which is beneficial to improving the design efficiency is carried out on the design type selection service of the power distribution network, then the target entity is extracted and constructed from the design drawing, and the design type selection knowledge pattern is constructed according to the predefined knowledge type, so that the design type selection knowledge pattern is benefited, and the efficiency of a designer in carrying out the design type selection work of the power distribution network can be greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are required for the embodiments will be briefly described, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope of the present invention. Like elements are numbered alike in the various figures.
Fig. 1 is a schematic flow chart of a method for constructing a design choice knowledge graph according to an embodiment of the present application;
fig. 2 is a schematic structural representation of design selection data in a method for constructing a design selection knowledge graph according to an embodiment of the present application;
fig. 3 is a schematic diagram of a pattern of a pattern selection knowledge pattern according to an embodiment of the present application;
fig. 4 is a flow chart of a method for designing an application method of a selection type knowledge graph according to an embodiment of the present application;
fig. 5 shows a schematic diagram of an apparatus module of a construction apparatus for designing a model selection knowledge graph according to an embodiment of the present application;
fig. 6 shows a schematic device module diagram of an application device for designing a pattern selection knowledge graph according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present invention.
The terms "comprises," "comprising," "including," or any other variation thereof, are intended to cover a specific feature, number, step, operation, element, component, or combination of the foregoing, which may be used in various embodiments of the present invention, and are not intended to first exclude the presence of or increase the likelihood of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the invention belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having a meaning that is the same as the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in connection with the various embodiments of the invention.
Example 1
Referring to fig. 1, a method flow diagram of a method for constructing a design selection type knowledge graph according to an embodiment of the present application is provided, where the method for constructing a design selection type knowledge graph according to an embodiment of the present application, as shown in fig. 1, includes:
step S101, obtaining a design material to be analyzed;
specifically, the design selection type knowledge graph provided by the embodiment can be applied to distribution network design in the field of power grids, and the associated information related to the legend in the design drawing is stored in the design selection type knowledge graph, so that the associated information related to the legend is called when the distribution network design is carried out, and corresponding material groups, materials, wiring schemes and wires are distributed for the legend.
The design material to be analyzed can be a design drawing and other files comprising design selection data, such as a dwg-format electric pole line design drawing. The embodiment does not limit the specific format of the design material to be analyzed, and can be set according to the actual application scene.
In the specific implementation process, the design material to be analyzed may include a large-scale online design scheme, or may include a design scheme of a user demarcating a range, and the obtaining manner of the design material to be analyzed may be set according to an actual application scenario, which is not limited in this embodiment.
Step S102, analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information;
specifically, after the design material to be analyzed is obtained, each item of design selection data in the design material to be analyzed is extracted according to a user-defined preset data structure.
For example, when extracting the legend information as the design selection data of the electric pole, the preset data structure may be as shown in fig. 2.
It should be noted that the legend information in this embodiment includes basic information related to the legend, such as a name, a bar number, a voltage level, and the like. The legend attribute information includes setting information related to the legend, such as geographical information attributes, sectional tower attributes, and pole attributes. The legend material information includes design choice information related to the legend, such as specification "JKLYJ-1-70" and name "overhead insulated conductor", etc. The legend wiring information is wire connection information related to legends, such as wire arrangement direction, wire type, wire arrangement mode, and the like.
In the implementation process, the type and the specific content of the design choice data may be determined according to an actual application scenario, and a designer may define the specific content of the obtained design choice data by customizing a preset data structure, which is not limited herein.
Step S103, extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity;
specifically, after the design selection data in all the design materials to be analyzed are obtained, part of the entities may be extracted from the design selection data, and part of the entities may be constructed based on the design selection data, so as to extract or construct n target entities, where the number of n is determined according to the actual application scenario, and is not specifically limited herein.
Specifically, the legend entity, the overhead line entity, the material entity, and the wire entity are target entities that can be directly extracted from the design choice data, and the material group entity and the overhead line relationship entity are target entities that are constructed based on a relationship between a material and a legend and a relationship between an overhead line and a legend.
In a specific implementation process, the legend entity can be obtained after the legend information is materialized, the material group entity and the material entity can be obtained after the legend material information is materialized, and the overhead line relation entity, the overhead line entity and the wire entity can be obtained after the legend overhead line information is materialized.
Specifically, as shown in fig. 3, the material group entity is an entity obtained by performing separate naming processing after materializing a complete material group information that can be adopted by a corresponding legend. Each legend may be associated with one or more material set entities, while each material set entity may be associated with multiple material entities, and different material set entities may be associated with the same material entity. For example, the legend entity consists of a Material 1 entity, a Material 2 entity, and a Material 3 entity.
The wiring relation entity is an entity obtained by carrying out independent naming treatment after carrying out materialization on the wiring scheme which can be adopted by the corresponding legend. Each of the wire-laying relation entities can be associated with a plurality of wire-laying modes, and each wire-laying mode can adopt the same wire or different wires. For example, the overhead line relation entity may associate an overhead line 1 entity and an overhead line 2 entity, while both the overhead line 1 entity and the overhead line 2 entity employ the same wire entity.
It should be noted that, in the actual use process, each legend is associated with one material group entity and one wiring relation entity, so that the scale of the design selection type knowledge graph can be effectively simplified.
According to a specific implementation manner of the embodiment of the present application, the constructing n target entities based on the design choice data includes:
and extracting and constructing n target entities based on the design selection data according to the knowledge representation mode of the attribute map entity.
In a specific embodiment, each target entity is constructed according to the attribute map entity construction mode, so that the scale of the design selection type knowledge graph can be effectively reduced, and the later development and utilization are facilitated.
Specifically, the step of constructing the target entity in the knowledge representation of the attribute map includes:
step 2, extracting detailed data associated with each type of entity from the data set of the design selection data;
step 4, uniquely naming each entity according to a preset naming rule;
and 5, storing the designated positions of the preset map database according to the types of the entities.
It should be noted that, for the material group entity, the materials are first materialized to obtain each material entity, then the detailed material information in the material group is replaced by the material entity name, and finally the material group entity is named, and the material group entity has no attribute.
For the overhead line relation entity, the overhead line scheme and the wire are materialized first, and then the detailed overhead line information and the wire information in the overhead line relation are replaced by the entity name of the overhead line scheme and the entity name of the wire. If the overhead line relation entity has a plurality of overhead line information and the wire entities corresponding to the overhead line entities are the same, naming distinction is needed to be made on the same overhead line scheme entity, and finally the overhead line relation entity is named, and the overhead line relation entity has no attribute.
By means of constructing the material group entity and the wiring relation entity, the design selection type knowledge graph is simpler, real business logic can be reflected more intuitively, and excessive material information and wiring information are not required to be displayed in the knowledge graph. The user can intuitively distinguish which materials are configured by the current legend and which wiring scheme is deployed by calling the material group entity.
In addition, in the application process, by calling the material group entity and the wiring relation entity, a user can match the corresponding material group entity through the legend entity and the wiring relation entity of the legend, so that the corresponding material entity, wiring entity and wire entity are directly configured for the legend, and the speed and efficiency of the design and the selection of the distribution network are effectively improved.
Step S104, a design selection type knowledge graph is constructed according to all target entities and the association relation among the target entities.
Specifically, each target entity comprises a corresponding association relation, namely an edge between each node of the knowledge graph.
As shown in fig. 3, the relationship between each node may be that a material 1 entity, a material 2 entity and a material 3 entity form a material group entity, the relationship between the material group entity and a legend entity is a selection type entity, the legend entity is associated with an overhead line relationship entity, the overhead line 1 entity and the overhead line 2 entity form an overhead line relationship entity, and both the overhead line 1 entity and the overhead line 2 entity adopt lead entities.
For example, the association relationship between the legend entity and the material group entity and the wire-drawing relationship entity is "association", the relationship between the material group entity and the material entity is "composition", the relationship between the wire-drawing relationship entity and the wire entity is "adoption", and the relationship between the entities can be as shown in table 1:
TABLE 1
| Entity | Relationship of | Entity |
| wiring_7 | By using | conductor_11 |
| pole_14 | Associated | Stringing scheme |
| pole_14 | Selecting | pole_selection_953 |
| Material | Composition of the composition | pole_selection_953 |
Specifically, wire_7 is the wire-up scheme, conductor_11 is the wire entity, pole_14 is the legend entity, pole_selection_953 is the material group entity.
It is to be appreciated that the association relationship between the entities can be adaptively set according to the actual application scenario.
According to a specific implementation manner of the embodiments of the present application, the constructing a design selection knowledge graph according to all target entities and association relations between the target entities includes:
combining different types of target entities according to the association relation among the target entities to obtain m atlas patterns corresponding to m legend entities, wherein m is a positive integer;
and storing the triples corresponding to each pattern mode into a preset pattern database to generate the design selection type knowledge pattern.
Specifically, the preset map database is a Neo4j map database.
In a specific embodiment, each legend entity has a corresponding one of the atlas patterns shown in FIG. 3.
In the pattern, the legend entity may be associated with a material group entity and an overhead line relationship entity, where one material group entity includes multiple material entities and one overhead line relationship entity includes multiple overhead line schemes, and each overhead line scheme has a corresponding wire entity.
The pattern mode can be adaptively expanded based on the association relation combination mode disclosed in the embodiment, which is not described in detail in the embodiment.
In the practical application process, after combining the target entities, the triple structures such as (legend entity, overhead line relation entity, material group entity), (material entity, composition, material group entity), (overhead line relation entity, overhead line scheme, overhead line entity), (overhead line entity, use, wire entity) and (legend entity, overhead line scheme, overhead line relation entity) can be obtained.
It should be noted that in the relationship between the head entity and the tail entity, corresponding attributes may be set, for example, the number attributes of the composition relationships in (material entity, composition, material group entity) may be set.
In the embodiment, a detailed description of how to construct a knowledge graph is omitted, and in the implementation, a knowledge graph construction mode corresponding to a Neo4j graph database may be used to perform the construction process of the embodiment, or a knowledge graph construction mode corresponding to other types of graph databases may be used to perform the construction process of the embodiment.
According to a specific implementation manner of the embodiments of the present application, after the design selection knowledge graph is constructed according to all the target entities and the association relationships between the target entities, the method further includes:
acquiring a newly added target entity;
updating the design selection type knowledge graph according to the type of the newly added legend entity;
if the newly added target entity is a newly added legend entity, a new pattern is constructed according to the newly added legend entity and the target entity related to the newly added legend entity, and triples corresponding to the pattern are stored in the preset map database so as to update the design selection type knowledge map;
if the newly added target entity is not the newly added legend entity, adding the newly added target entity into the corresponding pattern according to the type of the newly added target entity and the association relation with the corresponding pattern so as to update the design selection type knowledge pattern.
Specifically, the newly added target entity is a target entity not included in the current design selection type knowledge graph, and may be any one or more of a legend entity, a material group entity, a material entity, an overhead line relationship entity and a wire entity.
For example, the obtaining manner of the newly added target entity may be a new target entity in the distribution network design scheme created by the user in the process of using the design choice knowledge graph; and the design selection data added when the user updates the design selection knowledge graph according to the new design material can also correspond to the target entity. The embodiment does not specifically limit the acquisition mode of the newly added target entity, and can perform self-adaptive setting according to an actual application scene.
In the design choice knowledge graph provided in this embodiment, each legend entity has a corresponding graph mode. When a new target entity is added to the design selection type knowledge graph provided in this embodiment, it is required to determine whether the new target entity is a legend entity, and if the new target entity is a legend entity, a corresponding graph mode is required to be added to the design selection type knowledge graph to generate a new graph branch. If the new target entity is not the legend entity, the new target entity can be matched to the corresponding pattern in the current design selection type knowledge pattern, and the new target entity is added to the corresponding pattern according to the association relation corresponding to the type of the target entity. After the pattern corresponding to the legend entity is updated, the knowledge patterns of each pattern are constructed in a triplet mode.
According to the embodiment, the data volume of the design selection type knowledge graph is increased by continuously updating the design selection type knowledge graph, so that a designer can find the design selection type parameters matched with the legend in the knowledge graph more conveniently and more rapidly when using the design selection type knowledge graph.
In summary, the embodiment of the application provides a method for constructing a design selection type knowledge graph, and in the method, a material group entity and an overhead line relation entity are additionally arranged in the process of constructing the design selection type knowledge graph, so that the structure of the design selection type knowledge graph is effectively simplified, the material composition and the overhead line scheme type related to the legend can be displayed to a user more intuitively, and the efficiency of the user for carrying out power grid design selection can be effectively improved. In addition, in the embodiment, through carrying out materialization processing on various types of design selection data, in a mode of carrying out association combination according to materialization information of each entity, the construction quality of the design selection knowledge graph is effectively improved, the finally constructed design selection knowledge graph can truly reflect the knowledge of actual business, and the application of the distribution network design selection is more conveniently guided.
Example 2
Referring to fig. 4, a method flow diagram of an application method of a design selection type knowledge graph provided in an embodiment of the present application is shown in fig. 4, where the application method of the design selection type knowledge graph provided in the embodiment of the present application includes:
step S401, obtaining legend information to be queried and a query target;
step S402, analyzing the legend information to be queried to obtain a legend entity to be queried;
step S403, matching the target entity corresponding to the legend entity to be queried in the preset design choice knowledge graph, and deriving an output entity corresponding to the query target, where the output entity is at least one of a material group entity, an overhead line relationship entity, a material entity and a wire entity.
In a specific embodiment, the design selection type knowledge graph provided in embodiment 1 can be applied to any query system or power grid design system, so that a user can query and obtain corresponding material information and overhead line information in real time according to legend information.
Specifically, the query target may be material information or overhead line information, and may be adaptively set according to an actual application scenario.
In the implementation process, when a user performs power grid distribution network design, a legend message is added in a design drawing, and a system can automatically derive a material group and an overhead line relation associated with the legend message, wherein the material group comprises a plurality of types of materials, and the overhead line relation comprises a plurality of overhead line schemes and correspondingly adopted wire types. The user can complete the design selection of the legend according to the derived material group and the wiring relation.
According to a specific implementation manner of the embodiments of the present application, the matching the target entity corresponding to the legend entity to be queried in the preset design selection type knowledge graph, and deriving the output entity corresponding to the query target, includes:
acquiring a plurality of target entities corresponding to the legend entity to be queried, wherein each target entity comprises a historical use frequency attribute;
and sorting the target entities according to the historical use times attribute, and deriving the target entity with the largest historical use times as an output entity corresponding to the query target.
In the implementation process, the material information in the material group can be ranked according to the historical use times of the user of each material, and the user can select the material information with the highest historical use times as the material type of the current legend according to the ranking condition in the material group.
Specifically, the historical usage times of the user can be used as query attribute information to be stored in the attribute of the pattern mode corresponding to the design choice type knowledge pattern, so that the user can call the pattern mode when carrying out the query step.
It should be noted that, the attribute of the pattern mode corresponding to the design selection knowledge pattern may be adaptively configured according to the actual application scenario, which is not limited only herein.
In summary, the embodiment of the application provides an application method of a design selection type knowledge graph, which can apply the design selection type knowledge graph to a query system, so that a material group entity and an overhead line relation entity matched with a legend entity can be rapidly derived according to the legend entity input by a user, and the efficiency of the user for carrying out distribution network design selection is further improved.
Referring to fig. 5, a schematic device module diagram of a device 500 for constructing a design selection type knowledge graph according to an embodiment of the present application is provided, where the device 500 for constructing a design selection type knowledge graph according to an embodiment of the present application, as shown in fig. 5, includes:
a material acquisition module 501, configured to acquire a design material to be analyzed;
the material analysis module 502 is configured to analyze the design material to be analyzed to extract design selection data conforming to a preset data structure, where the design selection data includes legend information, legend attribute information, legend material information, and legend wiring information;
an entity construction module 503, configured to extract and construct n target entities based on the design choice data, where n is a positive integer, and the target entities include a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity, and a wire entity;
the map construction module 504 is configured to construct a design selection type knowledge map according to all target entities and the association relationship between the target entities.
Referring to fig. 6, a schematic device module diagram of an application device 600 for designing a pattern selection knowledge graph according to an embodiment of the present application is provided, where the application device 600 for designing a pattern selection knowledge graph according to an embodiment of the present application, as shown in fig. 6, includes:
the query acquisition module 601 is configured to acquire legend information to be queried and a query target;
the query analysis module 602 is configured to analyze the legend information to be queried to obtain a legend entity to be queried;
the map query module 603 is configured to match, in a preset design choice type knowledge map, a target entity corresponding to the legend entity to be queried, and derive an output entity corresponding to the query target, where the output entity is at least one of a material group entity, an overhead line relationship entity, an overhead line entity, a material entity, and a wire entity.
In addition, the embodiment of the application also provides a computer device, which comprises a processor and a memory, wherein the memory stores a computer program, and the computer program executes the design selection type knowledge graph construction method and the application method of the design selection type knowledge graph in the embodiment of the method when running on the processor.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program executes the design selection type knowledge graph construction method and the application method of the design selection type knowledge graph in the embodiment of the method when running on a processor.
In addition, the specific implementation process of the design selection type knowledge graph construction device, the application device of the design selection type knowledge graph, the computer device and the computer readable storage medium mentioned in the above embodiment may refer to the specific implementation process of the above method embodiment, and will not be described in detail herein.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other manners as well. The apparatus embodiments described above are merely illustrative, for example, of the flow diagrams and block diagrams in the figures, which illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules or units in various embodiments of the invention may be integrated together to form a single part, or the modules may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a smart phone, a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention.
Claims (10)
1. The construction method of the design selection type knowledge graph is characterized by comprising the following steps of:
obtaining a design material to be analyzed;
analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information;
extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity;
and constructing a design selection type knowledge graph according to all the target entities and the association relation among the target entities.
2. The method of claim 1, wherein the extracting and constructing n target entities based on the design choice data comprises:
and extracting and constructing n target entities based on the design selection data according to the knowledge representation mode of the attribute graph.
3. The method of claim 1, wherein the constructing a design choice knowledge graph according to all target entities and the association relationship between the target entities comprises:
combining different types of target entities according to the association relation among the target entities to obtain m atlas patterns corresponding to m legend entities, wherein m is a positive integer;
and storing the triples corresponding to each pattern mode into a preset pattern database to generate the design selection type knowledge pattern.
4. The method of claim 3, wherein after the design selection knowledge graph is constructed according to all target entities and the association relations among the target entities, the method further comprises:
acquiring a newly added target entity;
updating the design selection type knowledge graph according to the type of the newly added legend entity;
if the newly added target entity is a newly added legend entity, a new pattern is constructed according to the newly added legend entity and the target entity related to the newly added legend entity, and triples corresponding to the pattern are stored in the preset map database so as to update the design selection type knowledge map;
if the newly added target entity is not the newly added legend entity, adding the newly added target entity into the corresponding pattern according to the type of the newly added target entity and the association relation with the corresponding pattern so as to update the design selection type knowledge pattern.
5. An application method of a design selection type knowledge graph is characterized by comprising the following steps:
acquiring legend information to be queried and a query target;
analyzing the legend information to be queried to obtain a legend entity to be queried;
and matching target entities corresponding to the legend entities to be queried in a preset design selection type knowledge graph, and deriving output entities corresponding to the query targets, wherein the output entities are at least one of material group entities, overhead line relationship entities, overhead line entities, material entities and wire entities.
6. The method of claim 5, wherein the matching the target entity corresponding to the legend entity to be queried in the preset design choice knowledge graph and deriving the output entity corresponding to the query target comprises:
acquiring a plurality of target entities corresponding to the legend entity to be queried, wherein each target entity comprises a historical use frequency attribute;
and sorting the target entities according to the historical use times attribute, and deriving the target entity with the largest historical use times as an output entity corresponding to the query target.
7. The construction device for designing the model selection knowledge graph is characterized by comprising the following components:
the material acquisition module is used for acquiring the design material to be analyzed;
the material analysis module is used for analyzing the design material to be analyzed to extract design type selection data conforming to a preset data structure, wherein the design type selection data comprises legend information, legend attribute information, legend material information and legend wiring information;
the entity construction module is used for extracting and constructing n target entities based on the design selection data, wherein n is a positive integer, and the target entities comprise a legend entity, a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity;
and the map construction module is used for constructing a design selection type knowledge map according to all target entities and the association relation among all target entities.
8. An application device for designing a model selection knowledge graph is characterized by comprising:
the query acquisition module is used for acquiring the legend information to be queried and the query target;
the query analysis module is used for analyzing the legend information to be queried to obtain a legend entity to be queried;
and the map query module is used for matching the target entity corresponding to the legend entity to be queried in a preset design selection type knowledge map, and deriving an output entity corresponding to the query target, wherein the output entity is at least one of a material group entity, an overhead line relation entity, an overhead line entity, a material entity and a wire entity.
9. A computer device, characterized in that it comprises a processor and a memory, the memory storing a computer program, which when run on the processor performs the method of construction of the design choice knowledge graph of any one of claims 1 to 4 and the method of application of the design choice knowledge graph of claim 5 or 6.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program which, when run on a processor, performs the construction method of the design choice knowledge graph of any one of claims 1 to 4 and the application method of the design choice knowledge graph of claim 5 or 6.
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| CN117540915A (en) * | 2023-11-14 | 2024-02-09 | 南方电网调峰调频发电有限公司检修试验分公司 | Big data technology-based selection scheme generation method, device, equipment and medium |
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| CN117540915A (en) * | 2023-11-14 | 2024-02-09 | 南方电网调峰调频发电有限公司检修试验分公司 | Big data technology-based selection scheme generation method, device, equipment and medium |
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