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Report on the Workshop on Personal Knowledge Graphs (PKG 2021) at AKBC 2021

Authors:

Krisztian Balog,

Paramita Mirza,

Martin G. Skjæveland,

Zhilin WangAuthors Info & Claims

ACM SIGIR Forum, Volume 56, Issue 1

Article No.: 4, Pages 1 - 11

https://doi.org/10.1145/3582524.3582531

Published: 27 January 2023 Publication History

Abstract

The term personal knowledge graph (PKG) has been broadly used to refer to structured representation of information about a given user, primarily in the form of entities that are personally related to the user. The potential of personal knowledge graphs as a means of managing and organizing personal data, as well as a source of background knowledge for personalizing downstream services, has recently gained increasing attention from researchers in multiple fields, including that of Information Retrieval, Natural Language Processing, and the Semantic Web. The goal of the PKG'21 workshop was to create a forum for researchers and practitioners from diverse areas to present and discuss methods, tools, techniques, and experiences related to the construction and use of personal knowledge graphs, identify open questions, and create a shared research agenda. It successfully brought about a diverse workshop program, comprising an invited keynote, paper presentations, and breakout discussions, as a half-day event at the 3rd Automated Knowledge Base Construction (AKBC'21) conference. The workshop demonstrated that while the concept and research field of personal knowledge graphs is still in its early stages, there are many promising avenues of future development and research that already, and independently, have attracted the interest of several different communities.

Date: October 8, 2021.

Website: https://pkgs.ws.

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Cited By

Ain QChatti MMeteng Kamdem PAlatrash RJoarder SSiepmann C(2024)Learner Modeling and Recommendation of Learning Resources using Personal Knowledge GraphsProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636881(273-283)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636881
Ramosaj LBytyçi AShala BBytyçi E(2024)Graph and Structured Data Algorithms in Electronic Health Records: A Scoping ReviewMetadata and Semantic Research10.1007/978-3-031-65990-4_6(61-73)Online publication date: 31-Jul-2024
https://doi.org/10.1007/978-3-031-65990-4_6

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Published In

cover image ACM SIGIR Forum

ACM SIGIR Forum Volume 56, Issue 1

June 2022

109 pages

ISSN:0163-5840

DOI:10.1145/3582524

Issue’s Table of Contents

Copyright © 2023 Copyright is held by the owner/author(s).

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 27 January 2023

Published in SIGIR Volume 56, Issue 1

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Cited By

Ain QChatti MMeteng Kamdem PAlatrash RJoarder SSiepmann C(2024)Learner Modeling and Recommendation of Learning Resources using Personal Knowledge GraphsProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636881(273-283)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636881
Ramosaj LBytyçi AShala BBytyçi E(2024)Graph and Structured Data Algorithms in Electronic Health Records: A Scoping ReviewMetadata and Semantic Research10.1007/978-3-031-65990-4_6(61-73)Online publication date: 31-Jul-2024
https://doi.org/10.1007/978-3-031-65990-4_6

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