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Hauptverfasser: Skjæveland, Martin G., Balog, Krisztian, Bernard, Nolwenn, Łajewska, Weronika, Linjordet, Trond
Format: Preprint
Veröffentlicht: 2023
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Online-Zugang:https://arxiv.org/abs/2304.09572
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author Skjæveland, Martin G.
Balog, Krisztian
Bernard, Nolwenn
Łajewska, Weronika
Linjordet, Trond
author_facet Skjæveland, Martin G.
Balog, Krisztian
Bernard, Nolwenn
Łajewska, Weronika
Linjordet, Trond
contents This paper presents an ecosystem for personal knowledge graphs (PKGs), commonly defined as resources of structured information about entities related to an individual, their attributes, and the relations between them. PKGs are a key enabler of secure and sophisticated personal data management and personalized services. However, there are challenges that need to be addressed before PKGs can achieve widespread adoption. One of the fundamental challenges is the very definition of what constitutes a PKG, as there are multiple interpretations of the term. We propose our own definition of a PKG, emphasizing the aspects of (1) data ownership by a single individual and (2) the delivery of personalized services as the primary purpose. We further argue that a holistic view of PKGs is needed to unlock their full potential, and propose a unified framework for PKGs, where the PKG is a part of a larger ecosystem with clear interfaces towards data services and data sources. A comprehensive survey and synthesis of existing work is conducted, with a mapping of the surveyed work into the proposed unified ecosystem. Finally, we identify open challenges and research opportunities for the ecosystem as a whole, as well as for the specific aspects of PKGs, which include population, representation and management, and utilization.
format Preprint
id arxiv_https___arxiv_org_abs_2304_09572
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap
Skjæveland, Martin G.
Balog, Krisztian
Bernard, Nolwenn
Łajewska, Weronika
Linjordet, Trond
Artificial Intelligence
Information Retrieval
This paper presents an ecosystem for personal knowledge graphs (PKGs), commonly defined as resources of structured information about entities related to an individual, their attributes, and the relations between them. PKGs are a key enabler of secure and sophisticated personal data management and personalized services. However, there are challenges that need to be addressed before PKGs can achieve widespread adoption. One of the fundamental challenges is the very definition of what constitutes a PKG, as there are multiple interpretations of the term. We propose our own definition of a PKG, emphasizing the aspects of (1) data ownership by a single individual and (2) the delivery of personalized services as the primary purpose. We further argue that a holistic view of PKGs is needed to unlock their full potential, and propose a unified framework for PKGs, where the PKG is a part of a larger ecosystem with clear interfaces towards data services and data sources. A comprehensive survey and synthesis of existing work is conducted, with a mapping of the surveyed work into the proposed unified ecosystem. Finally, we identify open challenges and research opportunities for the ecosystem as a whole, as well as for the specific aspects of PKGs, which include population, representation and management, and utilization.
title An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap
topic Artificial Intelligence
Information Retrieval
url https://arxiv.org/abs/2304.09572