IP Library Granted Patent US 12,248,521
Granted Patent B1
US 12,248,521 · App. 18/456,999 · Granted Mar 11, 2025

Search using an overlay graph mapping to source knowledge graphs

Inventors: Rosario Uceda-Sosa (Hartsdale, NY); Guilherme Augusto Ferreira Lima (Campinas, BR); Achille Belly Fokoue-Nkoutche (White Plains, NY); Alexander Gray (Yonkers, NY); Maria Chang (Irvington, NY); Marcelo Machado (Rio de Janeiro, BR)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06F16/9038G06F16/90335
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,248,521
App. No.
18/456,999
Granted
Mar 11, 2025
Kind
B1
Abstract

Provided are techniques for a search using an overlay graph mapping to source knowledge graphs. A plurality of overlay graphs are generated, where each overlay graph comprises entities represented by nodes and relations represented by edges, and where the entities and the relations map to a subset of entities and relations in a plurality of source knowledge graphs. A search request comprising an entity and a relation is received. An overlay graph is selected from the plurality of overlay graphs based on the entity and the relation. The search request is issued against the overlay graph, where the search request is translated to knowledge graph specific queries, and where the knowledge graph specific queries are issued against the plurality of source knowledge graphs. Search results are received from the plurality of source knowledge graphs. The search results are used to respond to the search request.

Claims (60)

1. A computer-implemented method, comprising operations for:

generating a plurality of overlay graphs, wherein each overlay graph comprises entities represented by nodes, relations represented by edges, and mappings, wherein the mappings of each of the plurality of overlay graphs map the entities and the relations of that overlay graph to a subset of entities and relations in a plurality of source knowledge graphs, and wherein each of the plurality of overlay graphs is associated with logical rules that describe how to map new entities and new relations of the plurality of source knowledge graphs to that overlay graph;

receiving a search request comprising an entity and a relation;

selecting an overlay graph from the plurality of overlay graphs based on the entity and the relation of the search request;

issuing the search request against the overlay graph, wherein the search request is translated to knowledge graph specific queries, and wherein the knowledge graph specific queries are issued against the plurality of source knowledge graphs;

receiving search results from the plurality of source knowledge graphs; and

using the search results to respond to the search request.

2. The computer-implemented method of claim 1 , comprising operations for:

determining that a source knowledge graph of the plurality of source knowledge graphs has changed; and

using logical rules associated with the overlay graph to modify the overlay graph.

3. The computer-implemented method of claim 1 , comprising operations for:

translating the search request into a first query; and

identifying entities and relations of the first query that are also found in the plurality of source knowledge graphs.

4. The computer-implemented method of claim 3 , comprising operations for:

translating the first query into a second query based on the identified entities and relations; and

issuing the second query against the overlay graph to identify corresponding entities and relations in the overlay graph that correspond to the entities and the relations of the first query.

5. The computer-implemented method of claim 1 , wherein the plurality of source knowledge graphs comprise a plurality of ontological knowledge graphs, and wherein the overlay graph maps to the plurality of ontological knowledge graphs to present a single, unified, semantic view of the entities and the relations of the plurality of ontological knowledge graphs.

6. The computer-implemented method of claim 1 , wherein each of the mappings is associated with a probability.

7. The computer-implemented method of claim 1 , comprising operations for:

translating the search results into a format corresponding to 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:

generating a plurality of overlay graphs, wherein each overlay graph comprises entities represented by nodes, relations represented by edges, and mappings, wherein the mappings of each of the plurality of overlay graphs map the entities and the relations of that overlay graph to a subset of entities and relations in a plurality of source knowledge graphs, and wherein each of the plurality of overlay graphs is associated with logical rules that describe how to map new entities and new relations of the plurality of source knowledge graphs to that overlay graph;

receiving a search request comprising an entity and a relation;

selecting an overlay graph from the plurality of overlay graphs based on the entity and the relation of the search request;

issuing the search request against the overlay graph, wherein the search request is translated to knowledge graph specific queries, and wherein the knowledge graph specific queries are issued against the plurality of source knowledge graphs;

receiving search results from the plurality of source knowledge graphs; and

using the search results to respond to the search request.

9. The computer program product of claim 8 , wherein the program instructions executable by the processor to cause the processor to further perform operations for:

determining that a source knowledge graph of the plurality of source knowledge graphs has changed; and

using logical rules associated with the overlay graph to modify the overlay graph.

10. The computer program product of claim 8 , wherein the program instructions executable by the processor to cause the processor to further perform operations for:

translating the search request into a first query; and

identifying entities and relations of the first query that are also found in the plurality of source knowledge graphs.

11. The computer program product of claim 10 , wherein the program instructions executable by the processor to cause the processor to further perform operations for:

translating the first query into a second query based on the identified entities and relations; and

issuing the second query against the overlay graph to identify corresponding entities and relations in the overlay graph that correspond to the entities and the relations of the first query.

12. The computer program product of claim 8 , wherein the plurality of source knowledge graphs comprise a plurality of ontological knowledge graphs, and wherein the overlay graph maps to the plurality of ontological knowledge graphs to present a single, unified, semantic view of the entities and the relations of the plurality of ontological knowledge graphs.

13. The computer program product of claim 8 , wherein each of the mappings is associated with a probability.

14. The computer program product of claim 8 , comprising operations for:

translating the search results into a format corresponding to 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:

generating a plurality of overlay graphs, wherein each overlay graph comprises entities represented by nodes, relations represented by edges, and mappings, wherein the mappings of each of the plurality of overlay graphs map the entities and the relations of that overlay graph to a subset of entities and relations in a plurality of source knowledge graphs, and wherein each of the plurality of overlay graphs is associated with logical rules that describe how to map new entities and new relations of the plurality of source knowledge graphs to that overlay graph;

receiving a search request comprising an entity and a relation;

selecting an overlay graph from the plurality of overlay graphs based on the entity and the relation of the search request;

issuing the search request against the overlay graph, wherein the search request is translated to knowledge graph specific queries, and wherein the knowledge graph specific queries are issued against the plurality of source knowledge graphs;

receiving search results from the plurality of source knowledge graphs; and

using the search results to respond to the search request.

16. The computer system of claim 15 , wherein the program instructions further perform operations comprising:

determining that a source knowledge graph of the plurality of source knowledge graphs has changed; and

using logical rules associated with the overlay graph to modify the overlay graph.

17. The computer system of claim 15 , wherein the program instructions further perform operations comprising:

translating the search request into a first query; and

identifying entities and relations of the first query that are also found in the plurality of source knowledge graphs.

18. The computer system of claim 17 , wherein the program instructions further perform operations comprising:

translating the first query into a second query based on the identified entities and relations; and

issuing the second query against the overlay graph to identify corresponding entities and relations in the overlay graph that correspond to the entities and the relations of the first query.

19. The computer system of claim 15 , wherein the plurality of source knowledge graphs comprise a plurality of ontological knowledge graphs, and wherein the overlay graph maps to the plurality of ontological knowledge graphs to present a single, unified, semantic view of the entities and the relations of the plurality of ontological knowledge graphs.

20. The computer system of claim 15 , wherein each of the mappings is associated with a probability.

Assignments (2)
CONFIRMATORY LICENSE Recorded Dec 18, 2023
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: GOVERNMENT OF THE UNITED STATES AS REPRESENTED BY THE SECRETARY OF THE AIR FORCE
Reel/Frame 066058/0286 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 29, 2023
From: UCEDA-SOSA, ROSARIO; FERREIRA LIMA, GUILHERME AUGUSTO; FOKOUE-NKOUTCHE, ACHILLE BELLY; GRAY, ALEXANDER; CHANG, MARIA; MACHADO, MARCELO
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 064737/0042 →
References Cited (37)
US 8620931B2 · Zillner · 2013 [cited by applicant]
US 11531817B2 · Aditya · 2022 [cited by examiner]
US 20150095303A1 · Sonmez · 2015 [cited by examiner]
US 20200272624A1 · Aggour et al. · 2020 [cited by applicant]
US 20220129766A1 · Potts et al. · 2022 [cited by applicant]
US 20220129770A1 · Mihindukulasooriya · 2022 [cited by examiner]
US 20230350931A1 · Lewis · 2023 [cited by examiner]
WO 2004075466A2 · 2004 [cited by applicant]
WO 2020139861A1 · 2020 [cited by applicant]
Dai, et al., “A Knowledge-Based Service Composition Algorithm with Better QoS in Semantic Overlay,” Mathematical Problems in Engineering 2015 (2015), 7 pp. [cited by applicant]
Tarakci, et al., “UCASFUM: A Ubiquitous Context-Aware Semantic Fuzzy User Modeling System,” International Conference on Knowledge Engineering and Ontology Development, v. 2, Scitepress, 2012, pp. 278-283. [cited by applicant]
Soergel, “WordNet: An Electronic Lexical Database,” ResearchGate, Oct. 1998, 8 pp. [cited by applicant]
Speer, et al., “ConceptNet 5.5: An Open Multilingual Graph of General Knowledge,” Association for the Advancement of Artificial Intelligence, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2… [cited by applicant]
Xiao, et al., “Efficient Ontology-Based Data Integration with Canonical IRIs,” ESWC (2018), 15 pp. [cited by applicant]
Ullman, “Information Integration Using Logical Views,” Proceedings of the 6th International Conference on Database Theory. vol. 22, 1997, 22 pp. [cited by applicant]
Calvanese, et al., “The Mastri System for Ontology-based Data Access,” IOS Press, 2010, 11 pp. [cited by applicant]
Calvanese, et al., “Ontology-based Integration of Cross-linked Datasets,” In: SEMWEB (2015), 22 pp. [cited by applicant]
McGuinness, “OWL Web Ontology Language Guide”, ResearchGate, Jan. 2004, 22 pp. [cited by applicant]
Verborgh, et al., “Querying Datasets on the Web with High Availability,” Proceedings of the 13th International Semantic Web Conference. Lecture Notes in Computer Science, vol. 8796, 16 pp., Springer (Oct. 2014), http://… [cited by applicant]
Beckett, et al., “RDF 1.1 Turtle,” W3C recommendation, W3C (Feb. 25, 2014), 14 pp., http://www.w3.org/TR/2014/ REC-turtle-20140225/. [cited by applicant]
Hyland-Wood, “RDF 1.1 Concept and Abstract Syntax,” W3C recommendation, W3C (2014), 23 pp.,http://www.w3.org/TR/2014/REC-rdf11-concepts-20140225/. [cited by applicant]
Charalambidis, et al., “Semagrow: optimizing federated SPARQL queries,” ResearchGate, Sep. 2015, 9 pp., https://doi.org/10.1145/2814864.2814886. [cited by applicant]
Bonial, et al., “PropBank: Semantics of New Predicate Types,” Proceedings of the 9th edition of the Language Resources and Evaluation Conference (2014) 7 pp. [cited by applicant]
Brown, et al., “VerbNet Representations: Subevent Semantics for Transfer Verbs,” Proceedings of the First International Workshop on Designing Meaning Representations. 10 pp., Association for Computational Linguistics, F… [cited by applicant]
Xiao, “The Virtual Knowledge Graph System Ontop,” SEMWEB (2020) 4 pp. [cited by applicant]
Xiao, et al., “Virtual Knowledge Graphs: An Overview of Systems and Use Cases,” Chinese Academy of Sciences, 2019, 23 pp. [cited by applicant]
Verborgh, et al., “Web-Scale Querying through Linked Data Fragments,” Proceedings of the 7th Workshop on Linked Data on the Web. CEUR Workshop Proceedings, vol. 1184, 10 pp., (Apr. 2014), http://ceur-ws.org/Vol-1184/Ido… [cited by applicant]
Vrandecic, et al., “Wikidata: A Free Collaborative Knowledge Base,” Communications of the ACM 57(10), 8 pp., Oct. 2014). https://doi.org/10.1145/2629489. [cited by applicant]
DeMoura, et al., “Z3: An Efficient SMT Solver,” Microsoft Research, vol. 4963, 4 pp. (Apr. 2008). [cited by applicant]
“Federated knowledge graphs”, Wikimedia, [online][retrieved on Aug. 3, 2023] https://meta.wikimedia.org/wiki/Federated knowledge graphs, 6 pp. [cited by applicant]
“AgreementMakerLight/AMLProject: AgreementMakerLight Eclipse Project”, GitHub, [online][retrieved on Aug. 3, 2023] https://github.com/AgreementMakerLight/AML-Project, 3 pp. [cited by applicant]
“Maximize the Value of Your Data!”, Ontotext, [online][retrieved on Aug. 3, 2023] https://www.ontotext.com, 12 pp. [cited by applicant]
“Lexicon Model for Ontologies: Community Report”, Ontology-Lexicon Community Group, May 10, 2016, [online] [retrieved on Aug. 3, 2023] https://www.w3.org/2016/05/ontolex, 42 pp. [cited by applicant]
“Ontolex/lexinfo: LexInfo—Data Category Ontology for OntoLex-Lemon”, GitHub, [online][retrieved on Aug. 3, 2023] https://github.com/ontolex/lexinfo, 2 pp. [cited by applicant]
“Wikipedia: Contents/Categories”, Wikipedia, [online][retrieved on Aug. 4, 2023] https://en.wikipedia.org/wiki/Wikipedia:Contents/Categories, 9 pp. [cited by applicant]
“OWL 2 Web Ontology Language Document Overview (Second Edition)”, W3C, Dec. 11, 2012, [online][retrieved Aug. 21, 2023] https://www.w3.org/TR/2012/REC-owl2-overview-20121211/, 9 pp. [cited by applicant]
“Lexicon Model for Ontologies: Community Report”, Ontology-Lexicon Community Group, May 10 2016, [online] [retrieved on Aug. 3, 2023] https://www.w3.org/2016/05/ontolex, 84 pp. (submitted as PartA 42 pp. and PartB 42 pp… [cited by applicant]