Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

Research Organisations

External Research Organisations

  • German National Library of Science and Technology (TIB)
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Details

Original languageEnglish
Title of host publicationLinking Theory and Practice of Digital Libraries
Subtitle of host publication 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Proceedings
EditorsGerd Berget, Mark Michael Hall, Daniel Brenn, Sanna Kumpulainen
Pages141-152
Number of pages12
Publication statusPublished - 2021
Event25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021 - Virtual, Online
Duration: 13 Sept 202117 Sept 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12866 LNCS
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

Scientists always look for the most accurate and relevant answers to their queries in the literature. Traditional scholarly digital libraries list documents in search results, and therefore are unable to provide precise answers to search queries. In other words, search in digital libraries is metadata search and, if available, full-text search. We present a methodology for improving a faceted search system on structured content by leveraging a federation of scholarly knowledge graphs. We implemented the methodology on top of a scholarly knowledge graph. This search system can leverage content from third-party knowledge graphs to improve the exploration of scholarly content. A novelty of our approach is that we use dynamic facets on diverse data types, meaning that facets can change according to the user query. The user can also adjust the granularity of dynamic facets. An additional novelty is that we leverage third-party knowledge graphs to improve exploring scholarly knowledge.

Keywords

    Digital libraries, Faceted search, Information retrieval, Knowledge graph, Scholarly knowledge, Search system

ASJC Scopus subject areas

Cite this

Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. / Heidari, Golsa; Ramadan, Ahmad; Stocker, Markus et al.
Linking Theory and Practice of Digital Libraries : 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Proceedings. ed. / Gerd Berget; Mark Michael Hall; Daniel Brenn; Sanna Kumpulainen. 2021. p. 141-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12866 LNCS).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Heidari, G, Ramadan, A, Stocker, M & Auer, S 2021, Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. in G Berget, MM Hall, D Brenn & S Kumpulainen (eds), Linking Theory and Practice of Digital Libraries : 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12866 LNCS, pp. 141-152, 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Virtual, Online, 13 Sept 2021. https://doi.org/10.1007/978-3-030-86324-1_18
Heidari, G., Ramadan, A., Stocker, M., & Auer, S. (2021). Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. In G. Berget, M. M. Hall, D. Brenn, & S. Kumpulainen (Eds.), Linking Theory and Practice of Digital Libraries : 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Proceedings (pp. 141-152). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12866 LNCS). https://doi.org/10.1007/978-3-030-86324-1_18
Heidari G, Ramadan A, Stocker M, Auer S. Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. In Berget G, Hall MM, Brenn D, Kumpulainen S, editors, Linking Theory and Practice of Digital Libraries : 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Proceedings. 2021. p. 141-152. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2021 Jul 5. doi: 10.1007/978-3-030-86324-1_18
Heidari, Golsa ; Ramadan, Ahmad ; Stocker, Markus et al. / Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. Linking Theory and Practice of Digital Libraries : 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, Proceedings. editor / Gerd Berget ; Mark Michael Hall ; Daniel Brenn ; Sanna Kumpulainen. 2021. pp. 141-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "Scientists always look for the most accurate and relevant answers to their queries in the literature. Traditional scholarly digital libraries list documents in search results, and therefore are unable to provide precise answers to search queries. In other words, search in digital libraries is metadata search and, if available, full-text search. We present a methodology for improving a faceted search system on structured content by leveraging a federation of scholarly knowledge graphs. We implemented the methodology on top of a scholarly knowledge graph. This search system can leverage content from third-party knowledge graphs to improve the exploration of scholarly content. A novelty of our approach is that we use dynamic facets on diverse data types, meaning that facets can change according to the user query. The user can also adjust the granularity of dynamic facets. An additional novelty is that we leverage third-party knowledge graphs to improve exploring scholarly knowledge.",
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N1 - Funding Information: Acknowledgements. This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536) and the TIB Leibniz Information Centre for Science and Technology. The authors would like to thank Mohamad Yaser Jaradeh for helpful comments.

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