Identity resolution in knowledge graph databases

1. A method comprising:

presenting a user interface on a computing device, the user interface including:

an input element configured to receive an input of a search concept;

a similar concept selection element; and

a concept comparison portion;

executing a similarity search in a vector-space representation of a knowledge graph using the input, the knowledge graph storing subject, object, predicate triples;

populating the similar concept selection element with a set of a similar concepts based on a result of the executed similarity search, the set of similar concepts corresponding to a set of subjects in the knowledge graph;

receiving a selection of a comparison concept of the set of similar concepts from the similar concept selection element;

generating a predicate comparison visualization in the concept comparison portion based on predicates of the triples stored in the knowledge graph of the comparison concept and the search concept, wherein generating the predicate comparison visualization includes:

retrieving values of a subset of the predicates in the knowledge graph from triples stored in the knowledge graph of the search concept;

retrieving values of the subset of the predicates in the knowledge graph from triples stored in the knowledge graph of the comparison concept; and

for each respective predicate in the subset of the predicates:

selecting a similarity algorithm;

executing the similarity algorithm using the value of the respective predicate for the search concept compared with the value of the respective predicate for the comparison concept as inputs to the similarity algorithm;

receiving an output value of the similarity algorithm for the respective predicate; and

adding the value of the respective predicate for the comparison concept, the output value to the predicate comparison visualization, and the output value of the similarity algorithm to the predicate comparison visualization; and

presenting the predicate comparison visualization in the concept comparison portion.

2. The method of claim 1 , wherein selecting the similarity algorithm includes:

selecting the similarity algorithm based on a type of the respective predicate.

3. The method of claim 2 , wherein the respective predicate is a name and the similarity algorithm is a string similarity algorithm that performs a string compare on the value of the respective predicate for the search concept compared with the value of the respective predicate for the comparison concept.

4. The method of claim 2 , wherein the respective predicate is an address and the similarity algorithm is a distance comparison algorithm.

5. The method of claim 1 , wherein the predicate comparison visualization is formatted as a table.

6. The method of claim 5 , wherein a row in the table is formatted according to the output value.

7. The method of claim 1 , wherein the predicate comparison visualization is formatted as a graph, wherein the search concept is represented as a first node and the comparison concept is presented as a second node.

8. The method of claim 1 , wherein a degree of similarity is presented with each concept in the set of similar concepts in the similar concept selection element.

9. A non-transitory computer-readable medium comprising instructions, which when executed by at least one processor, configure the at least one processor to perform operations comprising:

presenting a user interface on a computing device, the user interface including:

an input element configured to receive an input of a search concept;

a similar concept selection element; and

a concept comparison portion;

executing a similarity search in a vector-space representation of a knowledge graph using the input, the knowledge graph storing subject, object, predicate triples;

populating the similar concept selection element with a set of a similar concepts based on a result of the executed similarity search, the set of similar concepts corresponding to a set of subjects in the knowledge graph;

receiving a selection of a comparison concept of the set of similar concepts from the similar concept selection element;

generating a predicate comparison visualization in the concept comparison portion based on predicates of the triples stored in the knowledge graph of the comparison concept and the search concept, wherein generating the predicate comparison visualization includes:

retrieving values of a subset of the predicates in the knowledge graph from triples stored in the knowledge graph of the search concept;

retrieving values of the subset of the predicates in the knowledge graph from triples stored in the knowledge graph of the comparison concept; and

for each respective predicate in the subset of the predicates:

selecting a similarity algorithm;

executing the similarity algorithm using the value of the respective predicate for the search concept compared with the value of the respective predicate for the comparison concept as inputs to the similarity algorithm;

receiving an output value of the similarity algorithm for the respective predicate; and

adding the value of the respective predicate for the comparison concept, the output value to the predicate comparison visualization, and the output value of the similarity algorithm to the predicate comparison visualization; and

presenting the predicate comparison visualization in the concept comparison portion.

10. The non-transitory computer-readable medium of claim 9 , wherein the operation of selecting the similarity algorithm includes:

selecting the similarity algorithm based on a type of the respective predicate.

11. The non-transitory computer-readable medium of claim 10 , wherein the respective predicate is a name and the similarity algorithm is a string similarity algorithm that performs a string compare on the value of the respective predicate for the search concept compared with the value of the respective predicate for the comparison concept.

12. The non-transitory computer-readable medium of claim 10 , wherein the respective predicate is an address and the similarity algorithm is a distance comparison algorithm.

13. The non-transitory computer-readable medium of claim 9 , wherein the predicate comparison visualization is formatted as a table.

14. The non-transitory computer-readable medium of claim 13 , wherein a row in the table is formatted according to the output value.

15. The non-transitory computer-readable medium of claim 9 , wherein the predicate comparison visualization is formatted as a graph, wherein the search concept is represented as a first node and the comparison concept is presented as a second node.

16. The non-transitory computer-readable medium of claim 9 , wherein a degree of similarity is presented with each concept in the set of similar concepts in the similar concept selection element.

17. A system comprising:

at least one processor; and

a storage device comprising instructions, which when executed by the at least one processor, configure the at least one processor to perform operations comprising:

presenting a user interface on a computing device, the user interface including:

an input element configured to receive an input of a search concept;

a similar concept selection element; and

a concept comparison portion;

executing a similarity search in a vector-space representation of a knowledge graph using the input, the knowledge graph storing subject, object, predicate triples;

populating the similar concept selection element with a set of a similar concepts based on a result of the executed similarity search, the set of similar concepts corresponding to a set of subjects in the knowledge graph;

receiving a selection of a comparison concept of the set of similar concepts from the similar concept selection element;

generating a predicate comparison visualization in the concept comparison portion based on predicates of the triples stored in the knowledge graph of the comparison concept and the search concept, wherein generating the predicate comparison visualization includes:

retrieving values of a subset of the predicates in the knowledge graph from triples stored in the knowledge graph of the search concept;

retrieving values of the subset of the predicates in the knowledge graph from triples stored in the knowledge graph of the comparison concept; and

for each respective predicate in the subset of the predicates:

selecting a similarity algorithm;

executing the similarity algorithm using the value of the respective predicate for the search concept compared with the value of the respective predicate for the comparison concept as inputs to the similarity algorithm;

receiving an output value of the similarity algorithm for the respective predicate; and

adding the value of the respective predicate for the comparison concept, the output value to the predicate comparison visualization, and the output value of the similarity algorithm to the predicate comparison visualization; and

presenting the predicate comparison visualization in the concept comparison portion.