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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Notes
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Open Research Knowledge Graph.
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Resource Description Framework.
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The basic reproduction number (R0) is the average number of infections produced by a single infectious person in a population with no immunity.
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Hierarchy of Geonames: https://www.geonames.org/export/place-hierarchy.html#hierarchy.
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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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Heidari, G., Ramadan, A., Stocker, M., Auer, S. (2021). Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. In: Berget, G., Hall, M.M., Brenn, D., Kumpulainen, S. (eds) Linking Theory and Practice of Digital Libraries. TPDL 2021. Lecture Notes in Computer Science(), vol 12866. Springer, Cham. https://doi.org/10.1007/978-3-030-86324-1_18
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