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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.07540 |
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| _version_ | 1866911775310479360 |
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| author | Bernard, Nolwenn Kostric, Ivica Łajewska, Weronika Balog, Krisztian Galuščáková, Petra Setty, Vinay Skjæveland, Martin G. |
| author_facet | Bernard, Nolwenn Kostric, Ivica Łajewska, Weronika Balog, Krisztian Galuščáková, Petra Setty, Vinay Skjæveland, Martin G. |
| contents | Personal knowledge graphs (PKGs) offer individuals a way to store and consolidate their fragmented personal data in a central place, improving service personalization while maintaining full user control. Despite their potential, practical PKG implementations with user-friendly interfaces remain scarce. This work addresses this gap by proposing a complete solution to represent, manage, and interface with PKGs. Our approach includes (1) a user-facing PKG Client, enabling end-users to administer their personal data easily via natural language statements, and (2) a service-oriented PKG API. To tackle the complexity of representing these statements within a PKG, we present an RDF-based PKG vocabulary that supports this, along with properties for access rights and provenance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_07540 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PKG API: A Tool for Personal Knowledge Graph Management Bernard, Nolwenn Kostric, Ivica Łajewska, Weronika Balog, Krisztian Galuščáková, Petra Setty, Vinay Skjæveland, Martin G. Human-Computer Interaction Artificial Intelligence Computation and Language Personal knowledge graphs (PKGs) offer individuals a way to store and consolidate their fragmented personal data in a central place, improving service personalization while maintaining full user control. Despite their potential, practical PKG implementations with user-friendly interfaces remain scarce. This work addresses this gap by proposing a complete solution to represent, manage, and interface with PKGs. Our approach includes (1) a user-facing PKG Client, enabling end-users to administer their personal data easily via natural language statements, and (2) a service-oriented PKG API. To tackle the complexity of representing these statements within a PKG, we present an RDF-based PKG vocabulary that supports this, along with properties for access rights and provenance. |
| title | PKG API: A Tool for Personal Knowledge Graph Management |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2402.07540 |