CN111090683B - Knowledge graph construction method and generation device thereof in engineering field - Google Patents
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Abstract
The invention discloses a knowledge graph construction method and a generation device thereof in the engineering field, wherein the construction method comprises the following steps: constructing an ontology layer of a knowledge graph applied to the engineering field, wherein the ontology layer comprises an ontology, an ontology attribute and an ontology relation; establishing a standard data table and collecting structural information; knowledge fusion is realized based on a database; the entity relationship between the entities inherits the ontology relationship between the ontologies corresponding to the entities. The invention has the advantages that: the method has the advantages that the real-time updating and traceability of the data are realized through the standard data table orientation linkage database, the speed and accuracy of knowledge cleaning are improved through the unique setting of the database, the entity in the engineering field is automatically extracted based on the ontology, and the construction efficiency and quality of the knowledge graph in the engineering field can be greatly improved.
Description
Technical Field
The invention belongs to the technical field of knowledge maps, and particularly relates to a knowledge map construction method and a knowledge map generation device in the engineering field.
Background
The knowledge graph is various entities or concepts and relations thereof existing in the real world, along with the rapid development of information technology, the data volume is increased in an explosive manner, and the knowledge graph extracts, correlates and integrates the data, so that the deep value of the large data is truly mined;
the knowledge graph can be divided into a general knowledge graph and a domain knowledge graph (also called a vertical knowledge graph), the general knowledge graph and the domain knowledge graph are based on Internet open data, the domain knowledge graph has a certain tolerance on the quality of knowledge extraction, the domain knowledge graph uses data in the domain or an enterprise as a main source, the knowledge extraction quality is very high, the knowledge extraction quality is more dependent on the combined extraction of structured, unstructured and semi-structured data in the enterprise, and the verification is carried out manually, so that the quality is ensured, wherein the engineering field has the characteristics of high risk, great harm and the like, and the requirement on the knowledge accuracy is particularly strict;
knowledge resources are core resources of knowledge-intensive enterprises such as engineering enterprises, and the competitive advantage of engineering enterprises is not in its fixed assets, but in the human and knowledge capital that it owns. The traditional knowledge base management in the engineering field generally adopts a document mode, the actual use efficiency is low, the knowledge scale is small, the knowledge graph carries out structuring treatment on the knowledge document, individual knowledge points are quickly called, but not documents containing the knowledge points, massive knowledge can be better classified and indexed, meanwhile, the method has good expandability, a large-scale knowledge base can be quickly built, and the quantity on the knowledge scale brings about quality change of knowledge utility.
In summary, traditional knowledge management in the engineering field is old and difficult to use, a threshold for knowledge accumulation is increased intangibly, the blank of an intelligent knowledge base in the engineering field is filled based on a knowledge graph technology, and meanwhile, how to establish a high-quality knowledge graph in the engineering field is needed to be solved.
Disclosure of Invention
The invention aims to provide a knowledge graph construction method and a generation device thereof in the engineering field according to the defects of the prior art, wherein the construction method is used for constructing a knowledge graph body layer applied to the engineering field, establishing a standard data table, collecting structured information, realizing knowledge fusion based on a database, and establishing entity and entity relation according to the body and the body relation, so that the problems that knowledge base management in the existing engineering field is unfavorable for knowledge accumulation and is difficult to be effectively used for application programs and effectively perform data reasoning are solved.
The invention is realized by the following technical scheme:
the construction method of the knowledge graph in the engineering field is characterized by comprising the following steps:
s1: constructing an ontology layer of a knowledge graph applied to the engineering field, wherein the ontology layer comprises an ontology, an ontology attribute and an ontology relation;
s2: establishing a standard data table and collecting structural information;
s3: knowledge fusion is realized based on a database;
s4: the entity relationship between the entities inherits the entity relationship between the entities corresponding to the entities;
s5: storing the ontology, the ontology attribute, the ontology relationship and the entity, the entity attribute and the entity relationship into a graph database, traversing the graph database, and merging the entities with the same entity name and the identical entity attribute;
s6: and updating the data of the graph database.
Step S2 comprises the steps of: establishing a standard data table, wherein the standard data table has a fixed format; extracting corresponding characters or values from semi-structured data and unstructured data in office documents, texts, pictures, drawings and reports according to the fixed format of the standard data table, and filling the corresponding characters or values into the standard data table; the standard data table is directionally stored in the database and directionally linked, and when the content of the data in the standard data table is modified, the data in the database is synchronously updated.
Step S3 comprises the steps of:
the database is pre-provided with a non-redundant data design form, the non-redundant data design form determines the uniqueness of each data field, and the data field is formed by combining a single field or a plurality of fields;
before the data in the standard data table is stored in the database, each data field in the standard data table is subjected to unique detection according to the non-redundant data design table and then is stored in the database.
The generation device relates to any one of the engineering field knowledge graph construction methods, and is characterized by comprising an information acquisition and update module, a data preprocessing module and an engineering field knowledge graph generation module, wherein:
the information acquisition and updating module acquires the semi-structured data and unstructured data of the entity through a standard data table and stores the semi-structured data and unstructured data into a database in real time, and acquires the structured data through the database; when the content of the data in the standard data table is modified, the data in the database is synchronously updated;
the data preprocessing module is pre-provided with a non-redundant data design form, the non-redundant data design form determines the uniqueness of each data field, and the data field is formed by combining a single field or a plurality of fields; before the data in the standard data table is stored in the database, each data field in the standard data table is subjected to uniqueness detection according to the non-redundant data design table and then is stored in the database;
the engineering field knowledge graph generation module inherits the ontology relations among the ontologies corresponding to the entities; and storing the ontology, the ontology attribute and the ontology relationship and the entity, the entity attribute and the entity relationship into a graph database, and traversing the graph database to merge the entities with the same entity name and the identical entity attribute.
The invention has the advantages that: the method has the advantages that the real-time updating and traceability of the data are realized through the standard data table orientation linkage database, the speed and accuracy of knowledge cleaning are improved through the unique setting of the database, the entity in the engineering field is automatically extracted based on the ontology, and the construction efficiency and quality of the knowledge graph in the engineering field can be greatly improved.
Drawings
FIG. 1 is a schematic flow chart of a knowledge graph construction method in the engineering field;
FIG. 2 is a schematic diagram of an ontology layer for constructing a security domain of an operation tunnel structure in the present invention;
FIG. 3 is a flow chart of the structured data storage in the relational database according to the present invention;
FIG. 4 is a diagram illustrating the establishment of an entity layer based on an ontology layer according to the present invention;
fig. 5 is a schematic structural diagram of a knowledge graph generating device in the engineering field.
Detailed Description
The features of the present invention and other related features are described in further detail below by way of example in conjunction with the following drawings, to facilitate understanding by those skilled in the art:
examples: as shown in fig. 1-5, the embodiment specifically relates to a method for constructing a knowledge graph in an engineering field and a generating device thereof, and the constructing method comprises the following steps:
(S1) constructing a knowledge graph ontology layer applied to the engineering field by combining field knowledge and expert experience, wherein the ontology layer comprises ontologies, ontology attributes and ontology relations, as shown in FIG. 2, wherein a square represents the ontologies, an ellipse represents the ontology attributes, and a diamond represents the ontology relations among the ontologies; the ontology, the ontology attributes and the ontology relationships included in the ontology layer are checked and verified by expert manual examination, so that rationality and full coverage are ensured.
(S2) establishing a standard data table which has a fixed format, wherein the fixed format is set according to the ontology in the ontology layer, the ontology attribute and the ontology relation, and collecting corresponding entities, entity attributes and entity relation to fill in; specifically, according to the fixed format requirement of the standard data table, extracting corresponding characters or values from the semi-structured data and unstructured data which are derived from office documents, texts, pictures, drawings and reports, and filling the corresponding characters or values into the standard data table; the standard data table is directionally stored in the database and is linked with the database, so that data structuring is realized, and meanwhile, structural analysis is carried out on the engineering field database, and related data is extracted; the linkage specifically means that once the content in the standard data table is modified, the relational database can be updated in real time, and a modification trace is reserved, so that the data modification can be traced.
For example, as shown in fig. 3, two standard data tables are established, namely, a tunnel attribute EXCEL standard data table and a monitoring engineering EXCEL standard data table, wherein the former is used for collecting entities and entity attributes of tunnel sections and tunnel segments, the latter is used for collecting entities and entity attributes of foundation pit engineering, foundation pit division and construction conditions, the entities and the attributes are derived from semi-structured or unstructured data such as web pages, documents and design drawings, the technical personnel fill out the semi-structured or unstructured data according to the standard data table, the standard data table is stored in a fixed position of a computer and is expressed in a fixed format, once the EXCEL unit cells record data, the data are synchronously updated to a database, and logs are reserved for the process of updating retrospective data; in addition, based on the engineering field database, the accessible database is subjected to structural analysis, and data such as stratum and tunnel segment are extracted.
(S3) realizing knowledge fusion based on the database, wherein the knowledge comprises semi-structured data and unstructured data acquired by a standard data table and structured data in the database;
as shown in fig. 3, a non-redundant data design form is preset in the database, the uniqueness of each data field is determined by the non-redundant data design form, and the data field is formed by combining a single field or a plurality of fields; before the data in the standard data table is stored in the database, each data field in the standard data table is subjected to uniqueness detection according to the non-redundant data design table and then is stored in the database;
for example, in the sections from the railway station of the Shanghai track traffic No. 2 line and the railway station of the Rainbow bridge No. 2 airport, and in the sections from the railway station of the Shanghai track traffic No. 10 line and the railway station of the Rainbow bridge No. 2 airport, if only the tunnel section name is used as the uniqueness detection, data can be omitted, and the line number and the tunnel section name can be used as the uniqueness detection combined field. The MySQL database uniqueness setting of the standard data table can be added when the table is built, and the uniqueness can be found out at a later stage and then the supplementary setting can be carried out.
(S4) the entity relationship between the entities inherits the entity relationship between the entities corresponding to the entities, a high-quality knowledge graph of the engineering field is established, the entity relationship inherits the entity relationship, the entity attribute is covered by the entity attribute, the entity relationship inherits the entity relationship, namely, the entity relationship is established by the entity to the entity, the entity relationship inherits the entity relationship, namely, the entity A of the entity A and the entity B are in the relationship C, the entity a of the entity A and the entity B of the entity B are in the relationship C, and the entity attribute covered by the entity attribute is the attribute contained by the entity and is more than or equal to the attribute possessed by the entity.
For example, as shown in fig. 4, based on the body of fig. 2, extracting corresponding entities from the relational database, and establishing an is_a relation one by one, such as the sea track traffic 10 line is_a track traffic, the national right road-pentagonal field is_a tunnel section, wherein the pipe segment 200 ring and the pipe segment 300 ring are the is_a tunnel pipe segments; the entity relationship inherits the body relationship, such as the tunnel section is_part_of rail transit, national right road-pentagonal field is_part_of Shanghai rail transit No. 10 line, tunnel segment is_part_of tunnel section, segment 200 ring and segment 300 ring are both is_part_of national right road-pentagonal field; the attribute of the body comprises and is more than or equal to the attribute of the entity, the rail transit has 2 attribute line numbers and running directions, the line number 10 of the rail transit on the entity is also provided with the same 2 attribute, the line number is 10, the running direction is upward, the tunnel interval has 5 attribute, the attribute is difficult to obtain due to the reasons of data confidentiality or record missing, and the like, and the actual national right line-pentagon field has 2 attribute, namely completion time 2010.4.10 and construction process soil pressure balance respectively.
And (S5) storing the ontology, the ontology attribute and the ontology relation and the entity, the entity attribute and the entity relation in the step S4 into a graph database, and traversing the graph database to merge the entities with the same entity name and the identical entity attribute.
(S6) further updating the knowledge graph, including data updating and mining of further relations. On one hand, foundation pit engineering is newly added near the rail transit, data are updated, and the knowledge graph also needs to be correspondingly updated; on the other hand, as professional cognition deepens or is combined with machine learning algorithms such as image data mining, deep learning and the like, new relations are further mined, and the knowledge graph also needs to be updated correspondingly.
According to the method, the system and the device, the ontology layer applied to the engineering field is built by combining field knowledge and expert experience, the standard data table is built, the structured information is collected, knowledge fusion is achieved based on the relational database, the entity and entity relation is built according to the ontology and the entity relation, the high-quality knowledge graph of the engineering field is built, and the problems that knowledge accumulation is not facilitated, the knowledge base management in the existing engineering field is difficult to effectively use for application programs, and data reasoning is effectively conducted are solved.
Fig. 5 shows a device for generating a knowledge graph of an engineering field in this embodiment, which includes:
A. and the information acquisition and updating module acquires the semi-structured and unstructured data of the entity through a standard data table, stores the semi-structured and unstructured data into a database in real time and acquires the structured data through an engineering field database.
B. And the data preprocessing module is used for carrying out knowledge cleaning and fusion through the unique setting of the data fields of the database and converting all the data into structured data.
C. And the engineering field knowledge graph generation module is used for extracting structured data converted by the database based on the mapping of the ontology layer and the entity layer, and storing the structured data in the graph database to generate the engineering field knowledge graph.
Claims (2)
1. The construction method of the knowledge graph in the engineering field is characterized by comprising the following steps:
s1: constructing an ontology layer of a knowledge graph applied to the engineering field, wherein the ontology layer comprises an ontology, an ontology attribute and an ontology relation;
s2: establishing a standard data table and collecting structural information;
establishing a standard data table, wherein the standard data table has a fixed format; the fixed format is set according to the ontology, the ontology attribute and the ontology relation in the ontology layer, and corresponding entities, the entity attribute and the entity relation are collected and filled in;
extracting corresponding characters or values from semi-structured data and unstructured data in office documents, texts, pictures, drawings and reports according to the fixed format of the standard data table, and filling the corresponding characters or values into the standard data table; the standard data table is directionally stored in the database and directionally linked, and when the content of the data in the standard data table is modified, the data in the database is synchronously updated;
s3: knowledge fusion is realized based on a database;
the database is pre-provided with a non-redundant data design form, the non-redundant data design form determines the uniqueness of each data field, and the data field is formed by combining a single field or a plurality of fields;
before the data in the standard data table is stored in the database, each data field in the standard data table is subjected to uniqueness detection according to the non-redundant data design table and then is stored in the database
S4: the entity relationship between the entities inherits the entity relationship between the entities corresponding to the entities;
establishing a knowledge graph in the engineering field, wherein the knowledge graph comprises an ontology and an entity, the entity relationship inherits the ontology relationship, the entity attribute covers the entity attribute, the ontology and the entity establish the dependency relationship to establish an is_a relationship between the ontology and the entity, the entity relationship inherits the ontology relationship to be that a relationship C exists between the ontology A and the entity B, and then a relationship C also exists between the entity a of the ontology A and the entity B of the ontology B, and the entity attribute covers the entity attribute to be that the attribute possessed by the ontology contains and is greater than or equal to the attribute possessed by the entity;
s5: storing the ontology, the ontology attribute, the ontology relationship and the entity, the entity attribute and the entity relationship into a graph database, traversing the graph database, and merging the entities with the same entity name and the identical entity attribute;
s6: and updating the data of the graph database.
2. The generating device related to the engineering field knowledge graph construction method of claim 1, characterized in that the generating device comprises an information acquisition and update module, a data preprocessing module and an engineering field knowledge graph generating module, wherein:
the information acquisition and updating module acquires the semi-structured data and unstructured data of the entity through a standard data table and stores the semi-structured data and unstructured data into a database in real time, and acquires the structured data through the database; when the content of the data in the standard data table is modified, the data in the database is synchronously updated;
the data preprocessing module is pre-provided with a non-redundant data design form, the non-redundant data design form determines the uniqueness of each data field, and the data field is formed by combining a single field or a plurality of fields; before the data in the standard data table is stored in the database, each data field in the standard data table is subjected to uniqueness detection according to the non-redundant data design table and then is stored in the database;
the engineering field knowledge graph generation module inherits the ontology relations among the ontologies corresponding to the entities; and storing the ontology, the ontology attribute and the ontology relationship and the entity, the entity attribute and the entity relationship into a graph database, and traversing the graph database to merge the entities with the same entity name and the identical entity attribute.
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| CN111708898A (en) * | 2020-06-13 | 2020-09-25 | 广州华建工智慧科技有限公司 | Intelligent construction information transmission method and system based on knowledge graph |
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| CN116097242A (en) | 2020-09-10 | 2023-05-09 | 西门子（中国）有限公司 | Knowledge graph construction method and device |
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