Performing a search using a hypergraph
Provided are techniques for performing a search using a hypergraph. Entities are identified. A knowledge graph using the entities is generated, wherein nodes of the knowledge graph represent the entities and edges between the nodes represent pair-wise relationships, and wherein each of the edges carries an edge score that quantifies a degree of coherence between a pair of the entities. A hypergraph using the knowledge graph is generated, wherein nodes of the hypergraph represent the entities and hyperedges represent relationships between multiple entities, and wherein each of the hyperedges carries a hyperedge score that quantifies a degree of coherence between the multiple entities. A search request is received. A search result is generated using the hypergraph, wherein the search result comprises a set of coherently related entities. The search result is returned.
1. A computer-implemented method, comprising operations for:
identifying entities;
generating a knowledge graph using the entities, wherein nodes of the knowledge graph represent the entities, wherein edges between the nodes represent pair-wise relationships, and wherein each of the edges carries an edge score that quantifies a degree of coherence between a pair of the entities;
generating a hypergraph by traversing the knowledge graph, wherein nodes of the hypergraph represent the entities, wherein hyperedges represent relationships between multiple entities, wherein each of the hyperedges carries a hyperedge score that quantifies a degree of coherence between the multiple entities, and wherein each of the hyperedges comprises a set of edges of the knowledge graph;
receiving a search request;
generating a search result using the hypergraph, wherein the search result comprises coherently related entities comprising the entities from at least one hyperedge of the hyperedges; and
returning the search result.
2. The computer-implemented method of claim 1 , wherein identifying the entities further comprises operations for:
performing named entity recognition to identify one or more of the entities in an information source.
3. The computer-implemented method of claim 1 , wherein the entities comprise one or more user-defined entities.
4. The computer-implemented method of claim 1 , wherein the edge score of a particular edge of the edges comprises a probabilistic edge score that is a function of proximity between locations of the entities in an information source, a length of the information source, and an entity type.
5. The computer-implemented method of claim 1 , wherein the hyperedge score of a particular hyperedge of the hyperedges comprises a probabilistic hyperedge score that is based on the edge score of each edge that is part of the particular hyperedge.
6. The computer-implemented method of claim 1 , wherein the coherently related entities comprise entities of an information source that are located in different portions of the information source.
7. The computer-implemented method of claim 1 , further comprising operations for:
identifying the hypergraph from a plurality of hypergraphs based on the search request.
8. A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations for:
identifying entities;
generating a knowledge graph using the entities, wherein nodes of the knowledge graph represent the entities, wherein edges between the nodes represent pair-wise relationships, and wherein each of the edges carries an edge score that quantifies a degree of coherence between a pair of the entities;
generating a hypergraph by traversing the knowledge graph, wherein nodes of the hypergraph represent the entities, wherein hyperedges represent relationships between multiple entities, wherein each of the hyperedges carries a hyperedge score that quantifies a degree of coherence between the multiple entities, and wherein each of the hyperedges comprises a set of edges of the knowledge graph;
receiving a search request;
generating a search result using the hypergraph, wherein the search result comprises coherently related entities comprising the entities from at least one hyperedge of the hyperedges; and
returning the search result.
9. The computer program product of claim 8 , wherein, for identifying the entities, the program instructions are executable by the processor to cause the processor to further perform:
performing named entity recognition to identify one or more of the entities in an information source.
10. The computer program product of claim 8 , wherein the entities comprise one or more user-defined entities.
11. The computer program product of claim 8 , wherein the edge score of a particular edge of the edges comprises a probabilistic edge score that is a function of proximity between locations of the entities in an information source, a length of the information source, and an entity type.
12. The computer program product of claim 8 , wherein the hyperedge score of a particular hyperedge of the hyperedges comprises a probabilistic hyperedge score that is based on the edge score of each edge that is part of the particular hyperedge.
13. The computer program product of claim 8 , wherein the coherently related entities comprise entities of an information source that are located in different portions of the information source.
14. The computer program product of claim 8 , wherein the program instructions are executable by the processor to cause the processor to further perform:
identifying the hypergraph from a plurality of hypergraphs based on the search request.
15. A computer system, comprising:
one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; and
program instructions, stored on at least one of the one or more computer-readable, tangible storage devices for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, to perform operations comprising:
identifying entities;
generating a knowledge graph using the entities, wherein nodes of the knowledge graph represent the entities, wherein edges between the nodes represent pair-wise relationships, and wherein each of the edges carries an edge score that quantifies a degree of coherence between a pair of the entities;
generating a hypergraph by traversing the knowledge graph, wherein nodes of the hypergraph represent the entities, wherein hyperedges represent relationships between multiple entities, wherein each of the hyperedges carries a hyperedge score that quantifies a degree of coherence between the multiple entities, and wherein each of the hyperedges comprises a set of edges of the knowledge graph;
receiving a search request;
generating a search result using the hypergraph, wherein the search result comprises coherently related entities comprising the entities from at least one hyperedge of the hyperedges; and
returning the search result.
16. The computer system of claim 15 , wherein, for identifying the entities, the program instructions further perform operations comprising:
performing named entity recognition to identify one or more of the entities in an information source.
17. The computer system of claim 15 , wherein the entities comprise one or more user-defined entities.
18. The computer system of claim 15 , wherein the edge score of a particular edge of the edges comprises a probabilistic edge score that is a function of proximity between locations of the entities in an information source, a length of the information source, and an entity type.
19. The computer system of claim 15 , wherein the hyperedge score of a particular hyperedge of the hyperedges comprises a probabilistic hyperedge score that is based on the edge score of each edge that is part of the particular hyperedge.
20. The computer system of claim 15 , wherein the coherently related entities comprise entities of an information source that are located in different portions of the information source.