Summarizing entity temporal evolution in knowledge graphs

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Mayesha Tasnim
  • Diego Collarana
  • Damien Graux
  • Fabrizio Orlandi
  • Maria Esther Vidal

Organisationseinheiten

Externe Organisationen

  • Rheinisch-Westfälische Technische Hochschule Aachen (RWTH)
  • Rheinische Friedrich-Wilhelms-Universität Bonn
  • Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme (IAIS)
  • Trinity College Dublin
  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
  • Universidad Simon Bolivar
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksThe Web Conference 2019
UntertitelCompanion of the World Wide Web Conference, WWW 2019
Herausgeber/-innenLing Liu, Ryen White
ErscheinungsortNew York
Seiten961-965
Seitenumfang5
ISBN (elektronisch)9781450366755
PublikationsstatusVeröffentlicht - 13 Mai 2019
Veranstaltung2019 World Wide Web Conference, WWW 2019 - San Francisco, USA / Vereinigte Staaten
Dauer: 13 Mai 201917 Mai 2019

Abstract

Knowledge graphs are dynamic in nature, new facts about an entity are added or removed over time. Therefore, multiple versions of the same knowledge graph exist, each of which represents a snapshot of the knowledge graph at some point in time. Entities within the knowledge graph undergo evolution as new facts are added or removed. The problem of automatically generating a summary out of different versions of a knowledge graph is a long-studied problem. However, most of the existing approaches are limited to a pairwise version comparison. This limitation makes it difficult to capture a complete evolution out of several versions of the same knowledge graph. To overcome this limitation, we envision an approach to create a summary graph capturing temporal evolution of entities across different versions of a knowledge graph. The entity summary graphs may then be used for documentation generation, profiling or visualization purposes. First, we take different temporal versions of a knowledge graph and convert them into RDF molecules. Secondly, we perform Formal Concept Analysis on these molecules to generate summary information. Finally, we apply a summary fusion policy in order to generate a compact summary graph which captures the evolution of entities.

ASJC Scopus Sachgebiete

Zitieren

Summarizing entity temporal evolution in knowledge graphs. / Tasnim, Mayesha; Collarana, Diego; Graux, Damien et al.
The Web Conference 2019: Companion of the World Wide Web Conference, WWW 2019. Hrsg. / Ling Liu; Ryen White. New York, 2019. S. 961-965.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Tasnim, M, Collarana, D, Graux, D, Orlandi, F & Vidal, ME 2019, Summarizing entity temporal evolution in knowledge graphs. in L Liu & R White (Hrsg.), The Web Conference 2019: Companion of the World Wide Web Conference, WWW 2019. New York, S. 961-965, 2019 World Wide Web Conference, WWW 2019, San Francisco, USA / Vereinigte Staaten, 13 Mai 2019. https://doi.org/10.1145/3308560.3316521
Tasnim, M., Collarana, D., Graux, D., Orlandi, F., & Vidal, M. E. (2019). Summarizing entity temporal evolution in knowledge graphs. In L. Liu, & R. White (Hrsg.), The Web Conference 2019: Companion of the World Wide Web Conference, WWW 2019 (S. 961-965). https://doi.org/10.1145/3308560.3316521
Tasnim M, Collarana D, Graux D, Orlandi F, Vidal ME. Summarizing entity temporal evolution in knowledge graphs. in Liu L, White R, Hrsg., The Web Conference 2019: Companion of the World Wide Web Conference, WWW 2019. New York. 2019. S. 961-965 doi: 10.1145/3308560.3316521
Tasnim, Mayesha ; Collarana, Diego ; Graux, Damien et al. / Summarizing entity temporal evolution in knowledge graphs. The Web Conference 2019: Companion of the World Wide Web Conference, WWW 2019. Hrsg. / Ling Liu ; Ryen White. New York, 2019. S. 961-965
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abstract = "Knowledge graphs are dynamic in nature, new facts about an entity are added or removed over time. Therefore, multiple versions of the same knowledge graph exist, each of which represents a snapshot of the knowledge graph at some point in time. Entities within the knowledge graph undergo evolution as new facts are added or removed. The problem of automatically generating a summary out of different versions of a knowledge graph is a long-studied problem. However, most of the existing approaches are limited to a pairwise version comparison. This limitation makes it difficult to capture a complete evolution out of several versions of the same knowledge graph. To overcome this limitation, we envision an approach to create a summary graph capturing temporal evolution of entities across different versions of a knowledge graph. The entity summary graphs may then be used for documentation generation, profiling or visualization purposes. First, we take different temporal versions of a knowledge graph and convert them into RDF molecules. Secondly, we perform Formal Concept Analysis on these molecules to generate summary information. Finally, we apply a summary fusion policy in order to generate a compact summary graph which captures the evolution of entities.",
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AU - Orlandi, Fabrizio

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