CN110825886A - Knowledge graph fusion system - Google Patents
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Abstract
The invention belongs to the technical field of artificial intelligence, and particularly relates to a knowledge graph fusion system. Compared with the prior art, the invention provides a knowledge fusion coordinator, a knowledge routing table generation process, knowledge routing updating, a knowledge routing notification process, a process of mounting the knowledge fusion coordinator by a single domain knowledge map server, a knowledge query forwarding process and the like. The technical scheme provided by the invention allows knowledge maps in various fields to be asynchronously constructed facing respective fields without considering ontology concepts of the comprehensive fields, realizes dynamic fusion application of the comprehensive fields through a knowledge fusion coordinator, and greatly improves the efficiency of the knowledge map fusion application, reduces repeated work and reduces cost because a single field does not need to construct comprehensive knowledge maps in related fields.
Description
Technical Field
The invention belongs to the technical field of artificial intelligence, and particularly relates to a knowledge graph fusion system.
Background
With the development of artificial intelligence and knowledge graph related technologies, more and more industry users begin to consider building knowledge graphs of respective professional fields in addition to common knowledge graph application parties such as google and Baidu. A small number of domain knowledge maps have been used to ground in industries such as government, public security, automotive, medical, and the like.
Different from a general knowledge graph, the domain knowledge graph has professionalism, generally faces to the application of a single professional domain, and does not realize cross-domain knowledge fusion. On the other hand, the cross-domain knowledge fusion is one of the future development directions of the knowledge graph and is a necessary way for the development of artificial intelligence. At present, due to technical limitation, under the condition of large ontology concept difference, the domain knowledge graph is difficult to realize the dynamic fusion of knowledge across domains like a general knowledge graph.
Referring to fig. 1, when a police department wishes to apply a police knowledge graph to assist in handling cases that police catch and flee together, there may be a need to query knowledge of a car graph, a weapon graph, a medicine graph, etc. Under the trend that the amount of knowledge is increasing day by day, it is not practical to integrate all knowledge into the public security knowledge map. How to realize the fusion application of the knowledge graph in the cross-domain becomes a problem to be solved urgently.
The existing knowledge graph fusion method is mainly oriented to the construction of knowledge graphs, and different knowledge graphs are fused into a larger knowledge graph. When the domain span of the knowledge graph is large, the number of the knowledge graphs is large, and the storage amount is large, knowledge structures in different domains are difficult to align and fuse.
After searching and inquiring the existing knowledge graph fusion patents, three typical patents are found to relate to the fusion of different knowledge graphs. The first patent "a large-scale knowledge-graph fusion method based on reduction anchor points" (application No. 201810780963.6), mainly includes: analyzing and preprocessing a large-scale knowledge graph; reduction set construction: calculating the similarity of semantic description documents between two knowledge graph entities; determining a positive reduction anchor point and a negative reduction anchor point; a mixed matching algorithm is used for predicting a large number of matching positions which do not need to be calculated in subsequent matching calculation according to the reduction anchor points; and extracting a matching result. The method adopts a reduction anchor point method to realize the fusion of the knowledge maps, and a larger knowledge map is formed after the fusion, so that the scene that different knowledge maps coexist for a long time does not exist.
The second patent "a neural network text classification method with multi-knowledge maps" (application number: 201810780502.9) mainly includes: inputting the texts in the training set into a long-term and short-term memory network to obtain context vectors of the texts; extracting entities from each text in the training set, and performing entity matching in the knowledge graph; respectively calculating attention weights of all matched entities and relations in the knowledge graph under the context vector to obtain an overall entity vector and an overall relation vector of the text, and further obtain a fact triple vector; calculating fact triple vectors under different knowledge maps, calculating attention weights of the fact triples to obtain text characterization vectors, inputting the text characterization vectors to a full connection layer of a neural network, and calculating the probability of each text belonging to each category by using a classifier to train the network; and predicting the category of the text to be predicted by using the trained deep neural network model. The method improves the comprehension of the model to the text semantics, and can classify the text contents more reliably, accurately and robustly. The knowledge graph fusion is realized by adopting a neural network text classification mode, a larger knowledge graph is formed after the fusion, and a scene that different knowledge graphs coexist for a long time does not exist.
The third patent, "a knowledge graph embedding method fusing multiple background knowledge" (application No.: 201710549884.X), mainly includes: 1) selecting high-quality entity description information from an entity label of a knowledge base, and selecting high-quality corpora related to the entity from Web corpora to form multi-background knowledge MCK; 2) learning an embedded representation of a knowledge base by embedding multi-context knowledge MCK; 3) obtaining semantic embedding vectors of corresponding entities from the MCK by using a DBALSTM model; wherein DBALSTM is depth D + bidirectional B + attention A + basic LSTM; 4) and applying a fusion embedding mechanism to fine-grained combination of MCK and RDF triples to complete knowledge graph embedding of fusion multi-background knowledge. The invention can improve the accuracy of knowledge graph embedding. The knowledge graph fusion is realized by embedding a multi-background knowledge MCK mode, a larger knowledge graph is formed after the fusion, and a scene that different knowledge graphs coexist for a long time does not exist.
In a word, no solution for realizing the cross-domain knowledge graph fusion through a knowledge routing mode exists at present.
Disclosure of Invention
Technical problem to be solved
The technical problem to be solved by the invention is as follows: how to provide a knowledge graph fusion system.
(II) technical scheme
In order to solve the above technical problem, the present invention provides a knowledge graph fusion system, including: the system comprises a knowledge map interface server, a knowledge fusion coordinator and a service application module; the knowledge fusion coordinator comprises: the system comprises a knowledge route generation module, a knowledge route updating module, a knowledge route query module and a knowledge route forwarding module;
the knowledge fusion coordinators are deployed according to the requirement, a plurality of knowledge fusion coordinators are deployed in a mesh shape to form a knowledge fusion coordinator network, and the routes of any two knowledge fusion coordinators in the mesh can reach;
and the knowledge map interface servers of the required field are mounted on the knowledge fusion coordinators, and each knowledge fusion coordinator respectively mounts the same/different number of knowledge map interface servers according to the performance;
wherein,
the knowledge fusion coordinator is used for acquiring a knowledge routing table from the Internet; the information is announced in the knowledge fusion coordinator network, and meanwhile, the knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
the service application module is used for initiating a knowledge query requirement to a self-owned knowledge map interface server of the domain to which the service application module belongs when a specific domain service application requirement appears, and forwarding the knowledge query requirement to a mounted knowledge fusion coordinator by the self-owned knowledge map interface server of the domain if the self-owned knowledge map interface server of the domain cannot meet the query requirement;
the knowledge fusion coordinator is also used for inquiring a knowledge routing table of the knowledge fusion coordinator when receiving a knowledge inquiry requirement, and forwarding the knowledge inquiry requirement to the knowledge fusion coordinator of the next hop of the route or a target knowledge map interface server;
and when the matched knowledge map interface server receives the knowledge query requirement in the field, returning the knowledge in the specific field according to the knowledge query requirement, and finally performing knowledge assembly and application by the service application module initiating the query.
The service application module is a service application APP.
The knowledge fusion coordinator acquires a knowledge routing table from the Internet;
the method specifically comprises the following steps: the knowledge route generation module is used for crawling the same entities in different fields from the Internet through a crawler, a manually set URL address list and an entity identification rule and filling an entity matching list; and the entity matching list is used as a cross-domain knowledge interface, and the next hop interface information of the knowledge fusion coordinator is added to form a knowledge routing table.
The method comprises the steps that notification is carried out in a knowledge fusion coordinator network, and meanwhile, a knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
the method specifically comprises the following steps: the knowledge route updating module is used for notifying in the knowledge fusion coordinator network after the knowledge route generating module of a certain knowledge fusion coordinator generates a knowledge route table, and notifying the knowledge route table to any knowledge fusion coordinator in the whole network; when the knowledge routing updating module of another knowledge fusion coordinator receives the knowledge routing table from another knowledge fusion coordinator, the information of the new knowledge routing table in the knowledge routing updating module is analyzed and extracted, and the information is updated to the knowledge routing table of the other knowledge fusion coordinator.
When receiving a knowledge query requirement, the knowledge fusion coordinator queries a knowledge routing table of the knowledge fusion coordinator, and forwards the knowledge query requirement to a knowledge fusion coordinator or a target knowledge map interface server of a next hop of a route;
the method specifically comprises the following steps:
the knowledge route query module is used for querying a knowledge route table of the knowledge route query module, and if the knowledge route query module queries a matched knowledge route which points to a knowledge map interface server which is mounted by the knowledge fusion coordinator and meets a query request, the knowledge route forwarding module returns the address information of a next-hop knowledge map interface server in the knowledge route to a service application module which initiates the query;
if the knowledge route query module queries the matched knowledge route, and the next hop of the matched knowledge route points to the reachable knowledge fusion coordinator of another route, the knowledge route forwarding module returns the address information of the next hop knowledge fusion coordinator in the knowledge route to the service application module initiating the query, and the service application module initiates a knowledge route query request to the address of the next hop knowledge fusion coordinator until the address of the matched knowledge map server is queried;
and the service application module initiates a knowledge query request to the knowledge graph server according to the queried matched knowledge graph server address, and the knowledge graph server returns matched knowledge to the service application module.
Wherein the knowledge fusion coordinator is a single device, in the case of a single device, a single module, a single server, or a cluster server.
Wherein the knowledge fusion coordinator is a plurality of devices, in which case the plurality of devices are directly connected or remotely connected.
Wherein the knowledge fusion coordinator is arranged in a net shape, a ring shape or a star shape under the condition of a plurality of devices.
And when the knowledge fusion coordinator is a plurality of devices, the path between any two devices can be reached.
The knowledge routing table is a routing information set queried by a knowledge map, and is used for returning a matching query result to a routing query party after receiving a knowledge routing query request, wherein the result is matched knowledge routing next hop information;
the knowledge routing table exists in the knowledge fusion coordinator, is generated and updated by the knowledge fusion coordinator, and is announced in a knowledge fusion coordinator network; the knowledge routes in the knowledge route table are arranged in an entry and at least comprise four columns of information, and the information in each knowledge route is specifically defined as follows:
(1) entity 1: querying entity names in the domain 1 knowledge graph in the request;
(2) the relationship is as follows: matching the entities in the domain 1 knowledge graph with the entities in the domain 2 knowledge graph;
(3) entity 2: name of an entity in a domain 2 knowledge graph;
(4) and (3) next jump: a domain 2 knowledge graph interface server or a routing can reach a knowledge fusion coordinator address of the domain 2 knowledge graph interface server.
(III) advantageous effects
Compared with the prior art, the invention provides a knowledge fusion coordinator, a knowledge routing table generation process, knowledge routing updating, a knowledge routing notification process, a process of mounting the knowledge fusion coordinator by a single domain knowledge map server, a knowledge query forwarding process and the like. The technical scheme provided by the invention allows knowledge maps in various fields to be asynchronously constructed facing respective fields without considering ontology concepts of the comprehensive fields, realizes dynamic fusion application of the comprehensive fields through a knowledge fusion coordinator, and greatly improves the efficiency of the knowledge map fusion application, reduces repeated work and reduces cost because a single field does not need to construct comprehensive knowledge maps in related fields.
Drawings
FIG. 1 is an exemplary diagram of a public security knowledge graph.
Fig. 2 is a schematic diagram of the technical scheme of the invention.
Fig. 3 is a knowledge routing representation.
Detailed Description
In order to make the objects, contents, and advantages of the present invention clearer, the following detailed description of the embodiments of the present invention will be made in conjunction with the accompanying drawings and examples.
In order to solve the problems of the prior art, the invention provides a knowledge graph fusion system, which comprises: the system comprises a knowledge map interface server, a knowledge fusion coordinator and a service application module; the knowledge fusion coordinator comprises: the system comprises a knowledge route generation module, a knowledge route updating module, a knowledge route query module and a knowledge route forwarding module;
the main functions of the knowledge fusion coordinator are to realize a cross-domain knowledge routing function, match knowledge query requirements of a service application module, and return a next hop interface of the coordinator to the service application module, wherein the interface points to other knowledge fusion coordinators which can be reached by the routing of the knowledge fusion coordinator or a knowledge map of a professional domain to be queried;
the knowledge routing table exists in a knowledge fusion coordinator, the knowledge fusion coordinator acquires the matching relation of the same entities across the fields through an entity identification rule set manually to form an entity matching relation, acquires knowledge routing advertisements of the knowledge fusion coordinator of the whole network through knowledge routing updating, and accordingly forms a self knowledge routing table and returns routing next hop information for each business application query;
as shown in fig. 2, the knowledge fusion coordinators are deployed in a certain number according to the requirement, and a plurality of knowledge fusion coordinators are deployed in a mesh form to form a knowledge fusion coordinator network, and any two knowledge fusion coordinators in the mesh can reach the routing;
the knowledge map interface servers in the required field are remotely mounted on the knowledge fusion coordinators through the Internet or other networks, and each knowledge fusion coordinator respectively mounts the same/different number of knowledge map interface servers according to the performance;
wherein,
the knowledge fusion coordinator is used for acquiring a knowledge routing table from the Internet through a correlation technique; the information is announced in the knowledge fusion coordinator network, and meanwhile, the knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
the service application module is used for initiating a knowledge query requirement to a self-owned knowledge map interface server of the domain to which the service application module belongs when a specific domain service application requirement appears, and forwarding the knowledge query requirement to a mounted knowledge fusion coordinator by the self-owned knowledge map interface server of the domain if the self-owned knowledge map interface server of the domain cannot meet the query requirement;
the knowledge fusion coordinator is also used for inquiring a knowledge routing table of the knowledge fusion coordinator when receiving a knowledge inquiry requirement, and forwarding the knowledge inquiry requirement to the knowledge fusion coordinator of the next hop of the route or a target knowledge map interface server;
and when the matched knowledge map interface server receives the knowledge query requirement in the field, returning the knowledge in the specific field according to the knowledge query requirement, and finally performing knowledge assembly and application by the service application module initiating the query.
The service application module is a service application APP.
The knowledge fusion coordinator acquires a knowledge routing table from the Internet through a correlation technique;
the method specifically comprises the following steps: the knowledge route generation module is used for crawling the same entities in different fields from the Internet through a crawler, a manually set URL address list and an entity identification rule and filling an entity matching list; and the entity matching list is used as a cross-domain knowledge interface, and the next hop interface information of the knowledge fusion coordinator is added to form a knowledge routing table.
The method comprises the steps that notification is carried out in a knowledge fusion coordinator network, and meanwhile, a knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
the method specifically comprises the following steps: the knowledge route updating module is used for notifying in the knowledge fusion coordinator network after the knowledge route generating module of a certain knowledge fusion coordinator generates a knowledge route table, and notifying the knowledge route table to any knowledge fusion coordinator in the whole network; when the knowledge routing updating module of another knowledge fusion coordinator receives the knowledge routing table from another knowledge fusion coordinator, the information of the new knowledge routing table in the knowledge routing updating module is analyzed and extracted, and the information is updated to the knowledge routing table of the other knowledge fusion coordinator.
When receiving a knowledge query requirement, the knowledge fusion coordinator queries a knowledge routing table of the knowledge fusion coordinator, and forwards the knowledge query requirement to a knowledge fusion coordinator or a target knowledge map interface server of a next hop of a route;
the method specifically comprises the following steps:
the knowledge route query module is used for querying a knowledge route table of the knowledge route query module, and if the knowledge route query module queries a matched knowledge route which points to a knowledge map interface server which is mounted by the knowledge fusion coordinator and meets a query request, the knowledge route forwarding module returns the address information of a next-hop knowledge map interface server in the knowledge route to a service application module which initiates the query;
if the knowledge route query module queries the matched knowledge route, and the next hop of the matched knowledge route points to the reachable knowledge fusion coordinator of another route, the knowledge route forwarding module returns the address information of the next hop knowledge fusion coordinator in the knowledge route to the service application module initiating the query, and the service application module initiates a knowledge route query request to the address of the next hop knowledge fusion coordinator until the address of the matched knowledge map server is queried;
and the service application module initiates a knowledge query request to the knowledge graph server according to the queried matched knowledge graph server address, and the knowledge graph server returns matched knowledge to the service application module.
The knowledge fusion coordinator may be a single device or a plurality of devices. The single device may be a single module, a single server or a cluster server, etc., and the form is not limited. The devices can be directly connected or remotely connected and are arranged in a net shape, an annular shape or a star shape, and a path between any two devices can be reached.
As shown in fig. 3, the knowledge routing table is a routing information set queried by the knowledge graph, and is configured to return a result of matching query to a routing querying party after receiving a knowledge routing query request, where the result is matching knowledge routing next hop information;
the knowledge routing table exists in the knowledge fusion coordinator, is generated, updated, stored and deleted by the knowledge fusion coordinator, and is announced and calculated in the knowledge fusion coordinator network; the knowledge routes in the knowledge route table are arranged in an entry and at least comprise four columns of information, and the information in each knowledge route is specifically defined as follows:
(1) entity 1 (domain 1): querying entity names in the domain 1 knowledge graph in the request;
(2) the relationship is as follows: matching the entities in the domain 1 knowledge graph with the entities in the domain 2 knowledge graph;
(3) entity 2 (domain 2): name of an entity in a domain 2 knowledge graph;
(4) and (3) next jump: a domain 2 knowledge graph interface server or a routing can reach a knowledge fusion coordinator address of the domain 2 knowledge graph interface server.
Further, the present invention provides a knowledge-graph fusion method implemented based on a knowledge-graph fusion apparatus including: the system comprises a knowledge map interface server, a knowledge fusion coordinator and a service application module; the knowledge fusion coordinator comprises: the system comprises a knowledge route generation module, a knowledge route updating module, a knowledge route query module and a knowledge route forwarding module;
the main functions of the knowledge fusion coordinator are to realize a cross-domain knowledge routing function, match knowledge query requirements of a service application module, and return a next hop interface of the coordinator to the service application module, wherein the interface points to other knowledge fusion coordinators which can be reached by the routing of the knowledge fusion coordinator or a knowledge map of a professional domain to be queried;
the knowledge routing table exists in a knowledge fusion coordinator, the knowledge fusion coordinator acquires the matching relation of the same entities across the fields through an entity identification rule set manually to form an entity matching relation, acquires knowledge routing advertisements of the knowledge fusion coordinator of the whole network through knowledge routing updating, and accordingly forms a self knowledge routing table and returns routing next hop information for each business application query;
as shown in fig. 2, the knowledge-graph fusion method includes the following steps:
step 1: deploying a certain number of knowledge fusion coordinators according to requirements, wherein the knowledge fusion coordinators are deployed in a mesh shape to form a knowledge fusion coordinator network, and the routes of any two knowledge fusion coordinators in the network can reach;
step 2: the method comprises the steps that a knowledge graph interface server in a required field is remotely mounted on knowledge fusion coordinators through the Internet or other networks, and each knowledge fusion coordinator respectively mounts the same or different number of knowledge graph interface servers according to performance;
and step 3: the knowledge fusion coordinator acquires a knowledge routing table from the Internet through a correlation technique; the information is announced in the knowledge fusion coordinator network, and meanwhile, the knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
and 4, step 4: when a specific domain service application requirement occurs, a domain service application module initiates a knowledge query requirement to a self-owned knowledge map interface server of the domain, and if the self-owned knowledge map interface server of the domain cannot meet the query requirement, the domain knowledge map interface server forwards the knowledge query requirement to a knowledge fusion coordinator mounted by the domain knowledge map interface server;
and 5: when receiving a knowledge query requirement, the knowledge fusion coordinator queries a knowledge routing table of the knowledge fusion coordinator, and forwards the knowledge query requirement to a knowledge fusion coordinator or a target knowledge map interface server of a next hop of a route;
step 6: and when the matched knowledge map interface server receives the knowledge query requirement in the field, returning the knowledge in the specific field according to the knowledge query requirement, and finally performing knowledge assembly and application by the service application module initiating the query.
The service application module is a service application APP.
The knowledge fusion coordinator acquires a knowledge routing table from the Internet through a correlation technique;
the method specifically comprises the following steps: the knowledge route generation module crawls the same entities in different fields from the Internet through a crawler, a manually set URL address list and an entity identification rule and fills an entity matching list; and the entity matching list is used as a cross-domain knowledge interface, and the next hop interface information of the knowledge fusion coordinator is added to form a knowledge routing table.
The method comprises the steps that notification is carried out in a knowledge fusion coordinator network, and meanwhile, a knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
the method specifically comprises the following steps: the knowledge route updating module is used for announcing in the knowledge fusion coordinator network after the knowledge route generating module of a certain knowledge fusion coordinator generates a knowledge route table, and announcing the knowledge route table to any knowledge fusion coordinator in the whole network; when the knowledge routing updating module of another knowledge fusion coordinator receives the knowledge routing table from another knowledge fusion coordinator, the information of the new knowledge routing table in the knowledge routing updating module is analyzed and extracted, and the information is updated to the knowledge routing table of the other knowledge fusion coordinator.
When receiving a knowledge query requirement, the knowledge fusion coordinator queries a knowledge routing table of the knowledge fusion coordinator, and forwards the knowledge query requirement to a knowledge fusion coordinator or a target knowledge map interface server of a next hop of a route;
the method specifically comprises the following steps: if the knowledge route query module queries a matched knowledge route, and the matched knowledge route points to a knowledge map interface server which is mounted by the knowledge fusion coordinator and meets the query request, the knowledge route forwarding module returns the address information of the next-hop knowledge map interface server in the knowledge route to the service application module which initiates the query;
if the knowledge route query module queries the matched knowledge route, and the next hop of the matched knowledge route points to the reachable knowledge fusion coordinator of another route, the knowledge route forwarding module returns the address information of the next hop knowledge fusion coordinator in the knowledge route to the service application module initiating the query, and the service application module initiates a knowledge route query request to the address of the next hop knowledge fusion coordinator until the address of the matched knowledge map server is queried;
and the service application module initiates a knowledge query request to the knowledge graph server according to the queried matched knowledge graph server address, and the knowledge graph server returns matched knowledge to the service application module.
The knowledge fusion coordinator may be a single device or a plurality of devices. The single device may be a single module, a single server or a cluster server, etc., and the form is not limited. The devices can be directly connected or remotely connected and are arranged in a net shape, an annular shape or a star shape, and a path between any two devices can be reached.
As shown in fig. 3, the knowledge routing table is a routing information set queried by the knowledge graph, and is configured to return a result of matching query to a routing querying party after receiving a knowledge routing query request, where the result is matching knowledge routing next hop information;
the knowledge routing table exists in the knowledge fusion coordinator, is generated, updated, stored and deleted by the knowledge fusion coordinator, and is announced and calculated in the knowledge fusion coordinator network; the knowledge routes in the knowledge route table are arranged in an entry and at least comprise four columns of information, and the information in each knowledge route is specifically defined as follows:
(1) entity 1 (domain 1): querying entity names in the domain 1 knowledge graph in the request;
(2) the relationship is as follows: matching the entities in the domain 1 knowledge graph with the entities in the domain 2 knowledge graph;
(3) entity 2 (domain 2): name of an entity in a domain 2 knowledge graph;
(4) and (3) next jump: a domain 2 knowledge graph interface server or a routing can reach a knowledge fusion coordinator address of the domain 2 knowledge graph interface server.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A knowledge graph fusion system, comprising: the system comprises a knowledge map interface server, a knowledge fusion coordinator and a service application module; the knowledge fusion coordinator comprises: the system comprises a knowledge route generation module, a knowledge route updating module, a knowledge route query module and a knowledge route forwarding module;
the knowledge fusion coordinators are deployed according to the requirement, a plurality of knowledge fusion coordinators are deployed in a mesh shape to form a knowledge fusion coordinator network, and the routes of any two knowledge fusion coordinators in the mesh can reach;
and the knowledge map interface servers of the required field are mounted on the knowledge fusion coordinators, and each knowledge fusion coordinator respectively mounts the same/different number of knowledge map interface servers according to the performance;
wherein,
the knowledge fusion coordinator is used for acquiring a knowledge routing table from the Internet; the information is announced in the knowledge fusion coordinator network, and meanwhile, the knowledge routing table of the knowledge fusion coordinator network is updated according to a set updating rule;
the service application module is used for initiating a knowledge query requirement to a self-owned knowledge map interface server of the domain to which the service application module belongs when a specific domain service application requirement appears, and forwarding the knowledge query requirement to a mounted knowledge fusion coordinator by the self-owned knowledge map interface server of the domain if the self-owned knowledge map interface server of the domain cannot meet the query requirement;
the knowledge fusion coordinator is also used for inquiring a knowledge routing table of the knowledge fusion coordinator when receiving a knowledge inquiry requirement, and forwarding the knowledge inquiry requirement to the knowledge fusion coordinator of the next hop of the route or a target knowledge map interface server;
and when the matched knowledge map interface server receives the knowledge query requirement in the field, returning the knowledge in the specific field according to the knowledge query requirement, and finally performing knowledge assembly and application by the service application module initiating the query.
2. The knowledge graph spectrum fusion system of claim 1, wherein the business application module is a business Application (APP).
3. The knowledge graph spectrum fusion system of claim 1, wherein the knowledge fusion coordinator obtains a knowledge routing table from the internet;
the method specifically comprises the following steps: the knowledge route generation module is used for crawling the same entities in different fields from the Internet through a crawler, a manually set URL address list and an entity identification rule and filling an entity matching list; and the entity matching list is used as a cross-domain knowledge interface, and the next hop interface information of the knowledge fusion coordinator is added to form a knowledge routing table.
4. The knowledge graph spectrum fusion system of claim 3, wherein the advertisement is performed in a knowledge fusion coordinator network, and the knowledge routing table of the knowledge fusion coordinator network is updated according to a set update rule;
the method specifically comprises the following steps: the knowledge route updating module is used for notifying in the knowledge fusion coordinator network after the knowledge route generating module of a certain knowledge fusion coordinator generates a knowledge route table, and notifying the knowledge route table to any knowledge fusion coordinator in the whole network; when the knowledge routing updating module of another knowledge fusion coordinator receives the knowledge routing table from another knowledge fusion coordinator, the information of the new knowledge routing table in the knowledge routing updating module is analyzed and extracted, and the information is updated to the knowledge routing table of the other knowledge fusion coordinator.
5. The knowledge graph and spectrum integration system of claim 4, wherein the knowledge integration coordinator queries its knowledge routing table when receiving the knowledge query requirement, and forwards the knowledge query requirement to the knowledge integration coordinator or the target knowledge graph interface server of the next hop of the route;
the method specifically comprises the following steps:
the knowledge route query module is used for querying a knowledge route table of the knowledge route query module, and if the knowledge route query module queries a matched knowledge route which points to a knowledge map interface server which is mounted by the knowledge fusion coordinator and meets a query request, the knowledge route forwarding module returns the address information of a next-hop knowledge map interface server in the knowledge route to a service application module which initiates the query;
if the knowledge route query module queries the matched knowledge route, and the next hop of the matched knowledge route points to the reachable knowledge fusion coordinator of another route, the knowledge route forwarding module returns the address information of the next hop knowledge fusion coordinator in the knowledge route to the service application module initiating the query, and the service application module initiates a knowledge route query request to the address of the next hop knowledge fusion coordinator until the address of the matched knowledge map server is queried;
and the service application module initiates a knowledge query request to the knowledge graph server according to the queried matched knowledge graph server address, and the knowledge graph server returns matched knowledge to the service application module.
6. The knowledge graph spectrum fusion system of claim 1, wherein the knowledge fusion coordinator is a single device, in the case of a single device, a single module, a single server, or a cluster server.
7. The knowledge graph spectrum fusion system of claim 1, wherein the knowledge fusion coordinator is a plurality of devices, in the case of a plurality of devices, a direct connection or a remote connection.
8. The knowledge graph spectrum fusion system of claim 7, wherein the knowledge fusion coordinator is a mesh, ring, or star arrangement in the case of multiple devices.
9. The knowledge graph spectrum fusion system of claim 1, wherein where the knowledge fusion coordinator is a plurality of devices, a path is enabled between any two devices.
10. The knowledge graph spectrum fusion system of claim 1, wherein the knowledge routing table is a set of routing information queried by the knowledge graph, and is configured to return a result of a matching query, which is matching knowledge routing next hop information, to a routing querying party after receiving a knowledge routing query request;
the knowledge routing table exists in the knowledge fusion coordinator, is generated and updated by the knowledge fusion coordinator, and is announced in a knowledge fusion coordinator network; the knowledge routes in the knowledge route table are arranged in an entry and at least comprise four columns of information, and the information in each knowledge route is specifically defined as follows:
(1) entity 1: querying entity names in the domain 1 knowledge graph in the request;
(2) the relationship is as follows: matching the entities in the domain 1 knowledge graph with the entities in the domain 2 knowledge graph;
(3) entity 2: name of an entity in a domain 2 knowledge graph;
(4) and (3) next jump: a domain 2 knowledge graph interface server or a routing can reach a knowledge fusion coordinator address of the domain 2 knowledge graph interface server.
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