CN111581399A

CN111581399A - Method, system, medium and equipment for dynamically calculating knowledge graph index rule

Info

Publication number: CN111581399A
Application number: CN202010521689.8A
Authority: CN
Inventors: 徐敏
Original assignee: Beijing Haizhi Xingtu Technology Co ltd
Current assignee: Beijing Haizhi Xingtu Technology Co ltd
Priority date: 2020-06-10
Filing date: 2020-06-10
Publication date: 2020-08-25

Abstract

The invention relates to a method, a system, a medium and equipment for dynamically calculating knowledge graph index rules, wherein the method comprises the following steps: determining a rule formula of the index rule; splicing the scenes into regular sentences according to the rule formula; splicing and assembling the rule statements and the related parameters to generate query conditions; and determining the value of the index rule according to the query condition. When a new index rule is added, index calculation does not need to be developed again, the existing interactive index rule is directly used for dynamic calculation, the development efficiency is greatly saved, and the requirements of interactivity, universality and complexity are met.

Description

Method, system, medium and equipment for dynamically calculating knowledge graph index rule

Technical Field

The invention relates to the field of knowledge graphs, in particular to a method, a system, a medium and equipment for dynamically calculating index rules of a knowledge graph.

Background

Indexes of various rules configured in the current knowledge graph can be calculated only by one rule, when new knowledge graph index rule calculation occurs, codes need to be re-developed for the index rule to calculate the rule, and the service scenes of interchangeability, universality and expandability of the index rule cannot be met.

Disclosure of Invention

The invention provides a method, a system, a medium and equipment for dynamically calculating index rules of a knowledge graph, aiming at solving the problems of interchangeability, trafficability and expansibility of index rule calculation of a knowledge graph which cannot be uniformly identified and calculated.

The technical scheme for solving the technical problems is as follows:

in a first aspect, the invention provides a method for dynamically calculating knowledge graph index rules, which comprises the following steps:

determining a rule formula of the index rule;

splicing the scenes into regular sentences according to the rule formula;

splicing and assembling the rule statements and the related parameters to generate query conditions;

and determining the value of the index rule according to the query condition.

On the basis of the technical scheme, the invention can be further improved as follows.

Further, the determining the value of the index rule according to the query condition specifically includes:

sending the query condition to a graph computation distributed engine to query computation resources;

and calculating the value of the index rule according to the query result returned by the graph calculation distributed engine.

Further, the graph computation distribution engine employs Spark graph.

Further, the method further comprises:

and writing the value of the index rule back to a database.

In a second aspect, the invention provides a knowledge graph index rule dynamic calculation system, which comprises the following modules:

the formula determining module is used for determining a rule formula of the index rule;

the sentence splicing module is used for splicing scenes into regular sentences according to the rule formula;

the condition generating module is used for splicing and assembling the rule statements and the related parameters to generate query conditions;

and the value determining module is used for determining the value of the index rule according to the query condition.

Further, the value determining module specifically includes:

the condition sending unit is used for sending the query condition to a query computing resource in a graph computing distributed engine;

and the value calculation unit is used for calculating the value of the index rule according to the query result returned by the graph calculation distributed engine.

Further, the graph computation distribution engine employs Spark graph.

Further, the above system further comprises:

and the value write-back module is used for writing back the value of the index rule to a database.

In a third aspect, the present invention also provides a computer-readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the above-mentioned method.

In a fourth aspect, the present invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the above method when executing the program.

The invention has the beneficial effects that: when a new index rule is added, index calculation does not need to be developed again, the existing interactive index rule is directly used for dynamic calculation, development efficiency is greatly saved, and the requirements of interactivity, universality and complexity are met.

Drawings

FIG. 1 is a flowchart of a method for dynamically calculating knowledge-graph index rules according to an embodiment of the present invention;

FIG. 2 is a block diagram of a software operation flow based on an embodiment of the method;

FIG. 3 is a block diagram of a knowledge graph index rule dynamic computing system according to the present invention.

Detailed Description

The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.

Fig. 1 is a flowchart of a method for dynamically calculating a knowledge graph index rule according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:

11. and determining a rule formula of the index rule.

In the step, a user configures rules on an interface, firstly, the universality of the rules is extracted according to the rules, a rule formula of an index rule is determined, and the interface converts the interface and a rear-end agreed interface according to the rules configured by the user.

12. And splicing the scenes into regular sentences according to the rule formula.

Specifically, the step may be implemented by a JAVA program, and the JAVA program may splice into rule statements recognizable by the algorithm in different scenes according to the index rule configured in the page in step 11, for example: object _ key, (v.field1/v.field2) as tag 1from edge1e left join field vertex1v on (concat _ ws ('/', 'vertex1', v.object _ key) ═ e.to _ key) "

13. And splicing and assembling the rule statements and the related parameters to generate query conditions.

Specifically, after the JAVA application splices the statements and related parameters of the rule, the JAVA application sends Spark graph x as a query condition to perform distributed query.

14. And determining the value of the index rule according to the query condition.

Step 14 may specifically include:

141. sending the query condition to a graph computation distributed engine to query computation resources;

142. and calculating the value of the index rule according to the query result returned by the graph calculation distributed engine.

Specifically, Spark graph is based on rule statements, parameter analysis, data value, and rule engine. And acquiring data resources required by calculation, acquiring the required value of the index rule by using an algorithm, and finally writing back the executed result to various databases.

Fig. 2 is a software operation flow diagram based on the embodiment of the method, and the meaning of each element in the diagram is as follows:

program-01: an application program written in the computer Java language;

program-02: a calculation module written based on a graph calculation distributed engine Spark graph;

DataCluster-01: a graph database cluster;

DB-01 to DB-n: a single database server in the spectrum database cluster;

flow-01: referring to the 3 rd step of the knowledge graph index calculation process, the process is to assemble the query conditions by Program-01 and deliver the query conditions to Program-02 for step 2 query;

flow-02: refer to the 4 th step of the knowledge graph offline query process, which is a process of querying and assembling final results by Program-02 using Spark graph x distribution.

Fig. 3 is a block diagram of a system for dynamically calculating knowledge graph index rules according to the present invention, where the functional principles of the modules in the system have been specifically introduced in the foregoing embodiment of the method, and are not described in detail below.

As shown in fig. 3, the system includes the following modules:

Optionally, in this embodiment, the value determining module specifically includes:

Optionally, in this embodiment, the graph computation distribution engine employs Spark graph;

optionally, in this embodiment, the system further includes:

An embodiment of the present invention further provides a computer-readable storage medium, including instructions, which, when executed on a computer, cause the computer to perform the method steps in the above method embodiment; or storing the instructions corresponding to the software modules of the system embodiments.

The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the method steps in the above method embodiments are implemented.

The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the modules and units in the above described system embodiment may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.

Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit 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 essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute 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), a magnetic disk or an optical disk, and other various media capable of storing program codes.

While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A dynamic calculation method for knowledge graph index rules is characterized by comprising the following steps:

determining a rule formula of the index rule;

splicing the scenes into regular sentences according to the rule formula;

and determining the value of the index rule according to the query condition.

2. The method according to claim 1, wherein the determining the value of the index rule according to the query condition specifically includes:

3. The method of claim 2, wherein the graph computation distribution engine employs Spark graph x.

4. The method for dynamically calculating knowledge-graph index rules according to any one of claims 1 to 3, further comprising:

and writing the value of the index rule back to a database.

5. A knowledge graph index rule dynamic computing system is characterized by comprising the following modules:

6. The system according to claim 5, wherein the value determining module specifically comprises:

7. The system of claim 6, wherein the graph computation distribution engine employs Spark graph x.

8. The system according to any one of claims 5 to 7, further comprising:

9. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the method of any of claims 1 to 4.

10. A computer 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 method according to any of claims 1 to 4 when executing the program.