CN114564515A - Unified storage method, device and medium for multi-version knowledge graph - Google Patents

Abstract

The invention discloses a unified storage method, a device and a medium for multi-version knowledge maps, wherein the method comprises the following steps: acquiring a plurality of knowledge map databases of different time versions based on the same ontology data source; adding time range attributes to all entities and relations based on a multi-version unified knowledge graph data structure according to the version time of the data of the knowledge graph, wherein the time range attributes comprise starting time and ending time; based on a knowledge map database with multiple versions and a uniform structure, calculating the difference relationship between knowledge maps of every two adjacent versions according to a difference comparison rule, and determining the evolution relationship of each entity; and updating the knowledge map database based on the knowledge map database of the first version according to the evolution relation, thereby constructing the knowledge map with multiple versions and unified storage. The invention can completely and accurately analyze the development elements of the autonomous traffic in each generation base, and can be widely applied to the technical fields of knowledge maps and data storage.

Description

A unified storage method, device and medium for multi-version knowledge graph

technical field

The invention relates to the technical field of knowledge graphs and data storage, in particular to a unified storage method, device and medium for multi-version knowledge graphs.

Background technique

The knowledge graph is essentially a structured semantic network knowledge base, including: directed graph structure, semantic relationships between entities represented by nodes and entities represented by edges. The knowledge graph is expanded from the initial semantic network through the data expansion of the graph structure, and finally the concept of knowledge graph is formed.

With the passage of time and the expansion of the ontology database, the relationship between entities and entities in the knowledge graph will continue to change, and the structure of the knowledge graph will change dynamically. Such a knowledge graph can be called a dynamic knowledge graph. By analyzing the knowledge graphs based on the same ontology data source, the same data structure, and different time versions, the evolution law of the knowledge graph can be inferred. At present, knowledge graph research at home and abroad mostly focuses on static knowledge graphs, and less attention on dynamic knowledge graphs. Regarding the storage of dynamic knowledge graphs, the existing mainstream method is still to store different versions of static knowledge graphs in the form of graphs. The existing methods have the disadvantages of high storage overhead, large redundancy of graph databases between different versions, and high complexity of evolution analysis.

In order to illustrate the usefulness of the unified knowledge graph, taking the intelligent transportation system as an example, with the improvement of the level of autonomy in some fields of the intelligent transportation system, it develops along the direction of "assisted autonomy-high autonomy-complete autonomy". The autonomous transportation system that divides the generation base according to the level of autonomy has become a major trend in the development of the transportation system. Based on the knowledge base of autonomous transportation system, extracting the elements and constructing the knowledge graph of each generation base can be used as an effective and common language in the development process of autonomous transportation system by humans and computers. However, the knowledge graph of each generation base is constructed separately, which cannot intuitively show the dynamic changes of the autonomous transportation system, and the evolution analysis process is complicated.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present invention provide a unified storage method, device and medium for a multi-version knowledge graph, which can store knowledge graphs of multiple versions in the same graph database.

One aspect of the present invention provides a unified storage method for a multi-version knowledge graph, including:

Based on the same ontology data source, multiple knowledge graph databases of different time versions are obtained, wherein the elements of the knowledge graph include a set of entities and relationships, as well as the attributes of each entity;

Based on the multi-version unified knowledge graph data structure, according to the version time of the knowledge graph data, add a time range attribute to all entities and relationships, and the time range attribute includes a start time and an end time;

Based on a knowledge graph database with multiple versions and a unified structure, according to the difference comparison rules, the difference relationship between the knowledge graphs of two adjacent versions is calculated, and the evolution relationship of each entity is determined;

Based on the first version of the knowledge graph database, according to the evolution relationship, the knowledge graph database is updated, so as to construct a multi-version unified storage knowledge graph.

Optionally, constructing a multi-version unified storage knowledge graph is specifically:

Build a knowledge graph based on the same ontology data source and different time versions;

Through the time range selection command, different versions of the knowledge graph can be restored;

Or, query the evolution path of an entity or relationship in different versions.

Optionally, the multi-version unified knowledge graph data structure is based on a common knowledge graph data structure, and a timestamp attribute is added to the entities and relationships based on the common knowledge graph data structure, and the timestamp attribute includes a start time and stop the time.

Optionally, the method also includes at least one of the following:

Determine the addition of entities of each group of adjacent versions according to the preset difference rules;

Or, according to a preset difference rule, determine the deletion of entities of each group of adjacent versions;

Or, according to the preset difference rule, determine the modification of the entity attributes of each group of adjacent versions;

Or, according to the preset difference rule, determine the modification of the relationship between the entities of each group of adjacent versions;

Or, according to a preset difference rule, determine the addition of the relationship between entities of each group of adjacent versions;

Or, according to a preset difference rule, the deletion of the relationship between entities of each group of adjacent versions is determined.

Optionally, the method also includes at least one of the following:

According to the evolution relationship rules, determine the addition of entities of each group of adjacent versions;

Or, according to the evolution relationship rule, determine the deletion of the entities of each group of adjacent versions;

Or, according to the evolution relationship rule, determine the update of the entity attributes of each group of adjacent versions;

Or, according to the evolution relationship rule, the update of the relationship between entities of each group of adjacent versions is determined.

Optionally, the knowledge graph database is updated based on the first version of the knowledge graph database according to the evolution relationship, including at least one of the following:

According to the evolution analysis results, add new entities;

Or, according to the evolution analysis result, add a new relationship;

Or, determine the start time attribute of the entity or relationship according to the version time of the current knowledge graph, if an entity or relationship appears for the first time in the current version of the knowledge graph, the value of the start time is recorded as the current version serial number;

Alternatively, the termination time attribute of an entity or relationship is determined according to the version time of the current knowledge graph. If an entity or relationship appears for the last time in the current version of the knowledge graph, the termination time attribute is recorded as the current version serial number.

Optionally, the method further includes:

In response to the time range selection command, the entities and relationships in the graph database are filtered according to the time attribute, the start time of the obtained entities and relationships is not greater than the specified version number, and the end time is not less than the specified version number, and the corresponding time range is filtered out. A single version or multiple versions of knowledge graph data for evolution analysis;

In response to the entity and relationship selection instruction, the entities and relationships in the graph database are filtered out corresponding single version or multiple versions of the entities and relationships according to the identifiers.

Another aspect of the embodiments of the present invention also provides a unified storage device for a multi-version knowledge graph, including:

The first module is used to obtain knowledge graph databases of multiple different time versions based on the same ontology data source, wherein the elements of the knowledge graph include a set of entities and relationships, and attributes of each entity;

The second module is used to add a time range attribute to all entities and relationships based on the version time of the knowledge map data based on the multi-version unified knowledge graph data structure, and the time range attribute includes a start time and an end time;

The third module is used to calculate the difference relationship between the knowledge maps of two adjacent versions based on the knowledge map database with multiple versions and a unified structure, according to the difference comparison rule, and determine the evolution relationship of each entity;

The fourth module is used to update the knowledge graph database based on the first version of the knowledge graph database according to the evolution relationship, so as to construct a multi-version unified storage knowledge graph.

Another aspect of the embodiments of the present invention further provides an electronic device, including a processor and a memory;

the memory is used to store programs;

The processor executes the program to implement the method as described above.

Another aspect of the embodiments of the present invention further provides a computer-readable storage medium, where the storage medium stores a program, and the program is executed by a processor to implement the aforementioned method.

The embodiment of the present invention also discloses a computer program product or computer program, where the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The computer instructions can be read from the computer readable storage medium by a processor of the computer device, and the processor executes the computer instructions to cause the computer device to perform the foregoing method.

The embodiment of the present invention obtains knowledge graph databases of multiple different time versions based on the same ontology data source, wherein the elements of the knowledge graph include a set of entities and relationships, as well as the attributes of each entity; based on a unified knowledge graph data structure of multiple versions , according to the version time of the data of the knowledge graph, add a time range attribute to all entities and relationships, and the time range attribute includes the start time and the end time; based on the knowledge graph database with multiple versions and a unified structure, according to the difference comparison rules , calculate the difference relationship between two adjacent versions of the knowledge map, and determine the evolution relationship of each entity; based on the knowledge map database of the first version, update the knowledge map database according to the evolution relationship, so as to build a multi-version unified storage knowledge map . The invention constructs multiple versions of the knowledge map database of the autonomous traffic system based on the unified knowledge map, and can completely and accurately analyze the development elements of the autonomous traffic in each generation base.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 is a flow chart of the overall steps provided by an embodiment of the present invention;

2 is a schematic diagram of a unified structure of a multi-version knowledge graph provided by an embodiment of the present invention;

3 is a schematic flowchart of a difference relationship comparison provided by an embodiment of the present invention;

Figure 4 is a schematic diagram of the knowledge map of the L3 level of driving automation;

Figure 5 is a schematic diagram of the knowledge graph at the L4 level of driving automation.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

In view of the problems existing in the prior art, an embodiment of the present invention provides a unified storage method for a multi-version knowledge graph, including:

Based on the same ontology data source, multiple knowledge graph databases of different time versions are obtained, wherein the elements of the knowledge graph include a set of entities and relationships, as well as the attributes of each entity;

Based on the multi-version unified knowledge graph data structure, according to the version time of the knowledge graph data, add a time range attribute to all entities and relationships, and the time range attribute includes a start time and an end time;

Based on a knowledge graph database with multiple versions and a unified structure, according to the difference comparison rules, the difference relationship between the knowledge graphs of two adjacent versions is calculated, and the evolution relationship of each entity is determined;

Based on the first version of the knowledge graph database, according to the evolution relationship, the knowledge graph database is updated, so as to construct a multi-version unified storage knowledge graph.

Optionally, constructing a multi-version unified storage knowledge graph is specifically:

Build a knowledge graph based on the same ontology data source and different time versions;

Through the time range selection command, different versions of the knowledge graph can be restored;

Or, query the evolution path of an entity or relationship in different versions.

Optionally, the multi-version unified knowledge graph data structure is based on a common knowledge graph data structure, and a timestamp attribute is added to the entities and relationships based on the common knowledge graph data structure, and the timestamp attribute includes a start time and stop the time.

Optionally, the method also includes at least one of the following:

Determine the addition of entities of each group of adjacent versions according to the preset difference rules;

Or, according to a preset difference rule, determine the deletion of entities of each group of adjacent versions;

Or, according to the preset difference rule, determine the modification of the entity attributes of each group of adjacent versions;

Or, according to the preset difference rule, determine the modification of the relationship between the entities of each group of adjacent versions;

Or, according to a preset difference rule, determine the addition of the relationship between entities of each group of adjacent versions;

Or, according to a preset difference rule, the deletion of the relationship between entities of each group of adjacent versions is determined.

Optionally, the method also includes at least one of the following:

According to the evolution relationship rules, determine the addition of entities of each group of adjacent versions;

Or, according to the evolution relationship rule, determine the deletion of the entities of each group of adjacent versions;

Or, according to the evolution relationship rule, determine the update of the entity attributes of each group of adjacent versions;

Or, according to the evolution relationship rule, the update of the relationship between entities of each group of adjacent versions is determined.

Optionally, the knowledge graph database is updated based on the first version of the knowledge graph database according to the evolution relationship, including at least one of the following:

According to the evolution analysis results, add new entities;

Or, according to the evolution analysis result, add a new relationship;

Or, determine the start time attribute of the entity or relationship according to the version time of the current knowledge graph, if an entity or relationship appears for the first time in the current version of the knowledge graph, the value of the start time is recorded as the current version serial number;

Alternatively, the termination time attribute of an entity or relationship is determined according to the version time of the current knowledge graph. If an entity or relationship appears for the last time in the current version of the knowledge graph, the termination time attribute is recorded as the current version serial number.

Optionally, the method further includes:

In response to the time range selection command, the entities and relationships in the graph database are filtered according to the time attribute, the start time of the obtained entities and relationships is not greater than the specified version number, and the end time is not less than the specified version number, and the corresponding time range is filtered out. A single version or multiple versions of knowledge graph data for evolution analysis;

In response to the entity and relationship selection instruction, the entities and relationships in the graph database are filtered out corresponding single version or multiple versions of the entities and relationships according to the identifiers.

Another aspect of the embodiments of the present invention also provides a unified storage device for a multi-version knowledge graph, including:

The first module is used to obtain knowledge graph databases of multiple different time versions based on the same ontology data source, wherein the elements of the knowledge graph include a set of entities and relationships, and attributes of each entity;

The second module is used to add a time range attribute to all entities and relationships based on the version time of the knowledge map data based on the multi-version unified knowledge graph data structure, and the time range attribute includes a start time and an end time;

The third module is used to calculate the difference relationship between the knowledge maps of two adjacent versions based on the knowledge map database with multiple versions and a unified structure, according to the difference comparison rule, and determine the evolution relationship of each entity;

The fourth module is used to update the knowledge graph database based on the first version of the knowledge graph database according to the evolution relationship, so as to construct a multi-version unified storage knowledge graph.

Another aspect of the embodiments of the present invention further provides an electronic device, including a processor and a memory;

the memory is used to store programs;

The processor executes the program to implement the method as described above.

Another aspect of the embodiments of the present invention further provides a computer-readable storage medium, where the storage medium stores a program, and the program is executed by a processor to implement the aforementioned method.

The embodiment of the present invention also discloses a computer program product or computer program, where the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The computer instructions can be read from the computer readable storage medium by a processor of the computer device, and the processor executes the computer instructions to cause the computer device to perform the foregoing method.

Below in conjunction with the accompanying drawings of the description, the specific implementation process and implementation principle of the present invention are described in detail:

1 shows a flowchart of a method for unified storage of multi-version knowledge graphs provided by an embodiment of the present invention, and the method includes:

Obtain knowledge graph databases of multiple different versions from the same ontology data source;

According to the difference calculation rule, determine the difference relationship table of the adjacent knowledge graph databases;

According to the difference relationship table, determine the evolution relationship table of the two adjacent knowledge graph databases;

Use the first version of the knowledge graph database as the basic database and store it in the graph database;

According to the evolution relationship table, update the graph database, including: adding new entities and relationships, updating the end time of entities and relationships, and updating the start time of entities and relationships.

Among them, a schematic structural diagram of the unified structure of the multi-version knowledge graph of the present invention is shown in FIG. 2 . The structure is based on a common knowledge graph data structure, and a timestamp attribute is added to the entities and relationships based on the common knowledge graph data structure. The timestamp property contains the start time and end time.

It should be noted that the ontology data source may be a CSV (Comma-Separated Values comma/character separated value) file and a database. When the data source is a database, the storage type is a graph database.

It should be noted that the difference comparison occurs when the data source is a CSV file, and the process is shown in FIG. 3 . The preset difference rules include at least one of the following:

If an entity or relationship of the previous version of the knowledge graph disappears in the next version, it is recorded as a difference relationship of deletion type;

When an entity or relationship appears for the first time in a certain version of the knowledge graph, it is recorded as a new type of difference relationship;

The attributes of an entity in the previous version of the knowledge graph are different from those of the next version, which is recorded as a combined difference relationship of deletion and new types.

For all entities and relationships in the pairwise adjacent knowledge graph databases, according to a preset difference rule, a set of all difference relations is obtained, representing the difference relation table of the pairwise adjacent knowledge graph databases.

According to the difference relationship, further determine the evolution relationship table of adjacent versions, including at least one of the following:

The difference relationship of deletion type is recorded as the evolution relationship of deletion type;

The difference relationship of the new type is recorded as the evolution relationship of the new type;

The combined difference relationship of deletion, addition and new type is recorded as the evolution relationship of update type.

It should be noted that the step of updating the graph database according to the evolution relation table includes at least one of the following:

Determine the termination time of the corresponding entity or relationship according to the evolution relationship of the deletion type;

Add a new corresponding entity or relationship according to the newly added type of evolution relationship;

According to the evolution relationship of the entity attribute update type, determine the termination time of the corresponding entity, back up the new corresponding entity, and modify the related attributes;

According to the evolution relationship of the update type of the relationship between entities, the termination time of the corresponding entity is determined, a new corresponding entity is backed up, and the related inter-entity relationship is modified.

It should be noted that the operation process of updating the graph database will not delete any data in the existing graph database, but retain the operation data of all versions. When the entity or relationship does not appear in the next version, update the data. The corresponding termination time will prevent the entity or relationship from being retrieved in the next version. When the attributes of the entity change, the end time of the original entity is updated, and the new entity is backed up, only the properties that need to be changed are updated, and the start time of the backup entity is updated.

Taking a specific knowledge graph version management as an example, the present invention will be further described in detail with reference to the accompanying drawings and specific data. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

Taking the autonomous driving-related ontology database as an example, SAE (Society of Automotive Engineer) defines the level of driving automation as L0 to L5. For different levels of autonomous driving, different versions of the knowledge map are constructed to represent each level. key technologies and driving environments required for autonomous driving. Figure 4 and Figure 5, wherein, Figure 4 represents the L3 level automatic driving knowledge map, and Figure 5 represents the L4 level automatic driving knowledge map.

First, after obtaining the knowledge graphs of level L0 to level L4, a total of 5 versions, compare the two adjacent knowledge graphs according to the difference rules, such as comparing the knowledge graphs of level L0 and level L1, comparing the knowledge graphs of level L1 and level L2, etc. and so on, respectively summarizing the difference relationship table. Then, according to the evolution analysis rules, an evolution relationship table is obtained. The results of the knowledge graph evolution relationship table of level L3 and level L4 are shown in Table 1.

Table 1

After summarizing the evolution relation table, first store the knowledge graph of level L0 in the graph database, and then update the graph database in turn according to the evolution relation table, then the knowledge graph data of levels L2 to L4 can be stored in the graph database, and finally get levels L0 to L4. Unified knowledge graph of 5 versions of level L4.

To sum up, the present invention first obtains multiple versions of the knowledge graph database, wherein the version data of the knowledge graph includes the information collections related to each entity and entity attributes required for expressing specific things, which are represented by nodes and relationships; Next, according to the difference relationship between the knowledge maps of the adjacent versions, determine the difference relationship table of the knowledge maps of each group of adjacent versions; then, according to the difference relationship table of the knowledge maps of the adjacent versions, determine the evolution of the adjacent versions of the groups Relation table; then, store the knowledge graph of the first version in the graph database, and update the graph database according to the evolution relation table of each group of adjacent versions. Based on different versions of the same knowledge map database, the invention further determines the evolution relationship according to the difference relationship between adjacent versions, stores the knowledge map database of each version in the same database uniformly, and can accurately restore the knowledge map database of each version, and Completely analyze the evolution relationship of the knowledge graph.

In some alternative implementations, the functions/operations noted in the block diagrams may occur out of the order noted in the operational diagrams. 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/operations involved. Furthermore, the embodiments presented and described in the flowcharts of the present invention are provided by way of example in order to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of the various operations are altered and in which sub-operations described as part of larger operations are performed independently.

Furthermore, while the invention is described in the context of functional modules, it is to be understood that, unless stated to the contrary, one or more of the described functions and/or features may be integrated in a single physical device and/or or software modules, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to understand the present invention. Rather, given the attributes, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the modules will be within the routine skill of the engineer. Accordingly, those skilled in the art, using ordinary skill, can implement the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are illustrative only and are not intended to limit the scope of the invention, which is to be determined by the appended claims along with their full scope of equivalents.

The functions, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk, etc. medium.

Logic and/or steps represented in flowcharts or otherwise described herein, for example, may be considered an ordered listing of executable instructions for implementing the logical functions, may be embodied in any computer-readable medium, For use with, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from and execute instructions from an instruction execution system, apparatus, or apparatus) or equipment. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in conjunction with an instruction execution system, apparatus, or apparatus.

More specific examples (non-exhaustive list) of computer readable media include the following: electrical connections with one or more wiring (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), Read Only Memory (ROM), Erasable Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, followed by editing, interpretation, or other suitable medium as necessary process to obtain the program electronically and then store it in computer memory.

It should be understood that various parts of the present invention may be implemented in hardware, software, firmware or a combination thereof. In the above-described embodiments, various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or a combination of the following techniques known in the art: Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.

In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structure, material or feature is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily 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.

Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, The scope of the invention is defined by the claims and their equivalents.

The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the described embodiments, and those skilled in the art can also make various equivalent deformations or replacements on the premise of not violating the spirit of the present invention, These equivalent modifications or substitutions are all included within the scope defined by the claims of the present application.

Claims (10)

1. A unified storage method of multi-version knowledge graph is characterized by comprising the following steps:

acquiring a plurality of knowledge graph databases of different time versions based on the same ontology data source, wherein elements of the knowledge graph comprise entities, a set of relations and attributes of each entity;

adding time range attributes to all entities and relations based on a multi-version unified knowledge graph data structure according to the version time of the data of the knowledge graph, wherein the time range attributes comprise starting time and ending time;

based on a knowledge map database with multiple versions and a uniform structure, calculating the difference relationship between knowledge maps of every two adjacent versions according to a difference comparison rule, and determining the evolution relationship of each entity;

and updating the knowledge map database based on the knowledge map database of the first version according to the evolution relation, thereby constructing the knowledge map with multiple versions and unified storage.

2. The method for uniformly storing multi-version knowledge graphs according to claim 1, wherein the method for constructing the multi-version knowledge graph for uniform storage specifically comprises the following steps:

constructing knowledge graphs based on the same ontology data source and different time versions;

through the time range selection instruction, the knowledge maps of different versions can be restored;

or querying the evolution path of a certain entity or relationship in different versions.

3. The method of claim 1, wherein the multi-version unified knowledge-graph data structure is based on a common knowledge-graph data structure, and timestamp attributes are added to the entities and relationships based on the common knowledge-graph data structure, wherein the timestamp attributes comprise a start time and an end time.

4. The method of claim 1, wherein the method further comprises at least one of:

determining addition of entities of each group of adjacent versions according to a preset difference rule;

or determining deletion of entities of each group of adjacent versions according to a preset difference rule;

or determining modification of the entity attributes of each group of adjacent versions according to a preset difference rule;

or determining the modification of the relationship between the entities of each group of adjacent versions according to a preset difference rule;

or determining addition of the relationship between the entities of each group of adjacent versions according to a preset difference rule;

or determining the deletion of the relationship between the entities of each group of adjacent versions according to a preset difference rule.

5. The method of claim 1, wherein the method further comprises at least one of:

determining addition of entities of each group of adjacent versions according to the evolution relation rule;

or determining deletion of each group of entities of adjacent versions according to the evolution relation rule;

or determining the updating of the entity attributes of each group of adjacent versions according to the evolution relation rule;

or determining the updating of the relationship between the entities of each group of adjacent versions according to the evolution relationship rule.

6. The method of claim 1, wherein the first version-based knowledge-graph database updates the knowledge-graph database according to an evolution relationship, and comprises at least one of:

adding a new entity according to the evolution analysis result;

or adding a new relationship according to the evolution analysis result;

or, determining the initial time attribute of the entity or relationship according to the version time of the current knowledge graph, and recording the value of the initial time as the sequence number of the current version if a certain entity or relationship appears in the knowledge graph of the current version for the first time;

or determining the ending time attribute of the entity or the relation according to the version time of the current knowledge graph, and recording the ending time attribute as the sequence number of the current version if a certain entity or relation appears in the knowledge graph of the current version for the last time.

7. The method of claim 1, wherein the method further comprises:

responding to a time range selection instruction, filtering the entities and the relations in the graph database according to time attributes, obtaining that the starting time of the entities and the relations is not more than the serial number of the appointed version, the ending time of the entities and the relations is not less than the serial number of the appointed version, filtering knowledge map data of a single version or a plurality of versions corresponding to the time range, and performing evolution analysis;

in response to the entity and relationship selection instructions, the entities and relationships in the graph database are filtered by the identifiers out of corresponding single or multiple versions of the entities and relationships.

8. A unified storage device for multi-version knowledge graphs, comprising:

the system comprises a first module, a second module and a third module, wherein the first module is used for obtaining a knowledge graph database of a plurality of different time versions based on the same ontology data source, and elements of the knowledge graph comprise entities, a set of relations and attributes of each entity;

a second module for adding time range attributes to all entities and relationships based on a multi-version unified knowledge graph data structure according to the version time of the data of the knowledge graph, the time range attributes including a start time and an end time;

the third module is used for calculating the difference relation between knowledge maps of every two adjacent versions based on a knowledge map database with a plurality of versions and a uniform structure according to a difference comparison rule and determining the evolution relation of each entity;

and the fourth module is used for updating the knowledge map database based on the knowledge map database of the first version according to the evolution relation so as to construct a knowledge map with multiple versions and unified storage.

9. An electronic device comprising a processor and a memory;

the memory is used for storing programs;

the processor executing the program realizes the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that the storage medium stores a program, which is executed by a processor to implement the method according to any one of claims 1 to 7.

Images