Swift logic for big data and knowledge graphs
Many modern companies wish to maintain knowledge in the form of a corporate knowledge graph and to use and manage this knowledge via a knowledge graph management system (KGMS). We formulate various requirements for a fully-fledged KGMS. In particular, such a system must be capable of performing comp...
| Príomhchruthaitheoirí: | , , , |
|---|---|
| Formáid: | Conference item |
| Foilsithe / Cruthaithe: |
Association for the Advancement of Artificial Intelligence
2017
|
| _version_ | 1826265751315546112 |
|---|---|
| author | Bellomarini, L Gottlob, G Pieris, A Sallinger, E |
| author_facet | Bellomarini, L Gottlob, G Pieris, A Sallinger, E |
| author_sort | Bellomarini, L |
| collection | OXFORD |
| description | Many modern companies wish to maintain knowledge in the form of a corporate knowledge graph and to use and manage this knowledge via a knowledge graph management system (KGMS). We formulate various requirements for a fully-fledged KGMS. In particular, such a system must be capable of performing complex reasoning tasks but, at the same time, achieve efficient and scalable reasoning over Big Data with an acceptable computational complexity. Moreover, a KGMS needs interfaces to corporate databases, the web, and machinelearning and analytics packages. We present KRR formalisms and a system achieving these goals. |
| first_indexed | 2024-03-06T20:28:34Z |
| format | Conference item |
| id | oxford-uuid:304489bd-f47b-4e69-a7ba-54f8ba43ea35 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T20:28:34Z |
| publishDate | 2017 |
| publisher | Association for the Advancement of Artificial Intelligence |
| record_format | dspace |
| spelling | oxford-uuid:304489bd-f47b-4e69-a7ba-54f8ba43ea352022-03-26T13:00:22ZSwift logic for big data and knowledge graphsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:304489bd-f47b-4e69-a7ba-54f8ba43ea35Symplectic Elements at OxfordAssociation for the Advancement of Artificial Intelligence2017Bellomarini, LGottlob, GPieris, ASallinger, EMany modern companies wish to maintain knowledge in the form of a corporate knowledge graph and to use and manage this knowledge via a knowledge graph management system (KGMS). We formulate various requirements for a fully-fledged KGMS. In particular, such a system must be capable of performing complex reasoning tasks but, at the same time, achieve efficient and scalable reasoning over Big Data with an acceptable computational complexity. Moreover, a KGMS needs interfaces to corporate databases, the web, and machinelearning and analytics packages. We present KRR formalisms and a system achieving these goals. |
| spellingShingle | Bellomarini, L Gottlob, G Pieris, A Sallinger, E Swift logic for big data and knowledge graphs |
| title | Swift logic for big data and knowledge graphs |
| title_full | Swift logic for big data and knowledge graphs |
| title_fullStr | Swift logic for big data and knowledge graphs |
| title_full_unstemmed | Swift logic for big data and knowledge graphs |
| title_short | Swift logic for big data and knowledge graphs |
| title_sort | swift logic for big data and knowledge graphs |
| work_keys_str_mv | AT bellomarinil swiftlogicforbigdataandknowledgegraphs AT gottlobg swiftlogicforbigdataandknowledgegraphs AT pierisa swiftlogicforbigdataandknowledgegraphs AT sallingere swiftlogicforbigdataandknowledgegraphs |