Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28033
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Gottron, Thomas
Knauf, Malte
Scherp, Ansgar
Schaible, Johann
Title: ELLIS: Interactive exploration of Linked Data on the level of induced schema patterns
Editor(s): Thalhammer, A
Cheng, G
Gunaratna, K
Citation: Gottron T, Knauf M, Scherp A & Schaible J (2016) ELLIS: Interactive exploration of Linked Data on the level of induced schema patterns. In: Thalhammer A, Cheng G & Gunaratna K (eds.) Summarizing and Presenting Entities and Ontologies: Proceedings of the 2nd International Workshop on Summarizing and Presenting Entities and Ontologies (SumPre 2016) co-located with the 13th Extended Semantic Web Conference (ESWC 2016), volume 1605. CEUR Workshop Proceedings, 1605. SumPre 2016 - 2nd International Workshop on Summarizing and Presenting Entities and Ontologies, 30.05.2016-30.05.2016. Anissaras: CEUR Workshop Proceedings. http://ceur-ws.org/Vol-1605/
Issue Date: 2016
Date Deposited: 22-Oct-2018
Series/Report no.: CEUR Workshop Proceedings, 1605
Conference Name: SumPre 2016 - 2nd International Workshop on Summarizing and Presenting Entities and Ontologies
Conference Dates: 2016-05-30 - 2016-05-30
Abstract: We present ELLIS, a demo to browse the Linked Data cloud on the level of induced schema patterns. To this end, we define schema-level patterns of RDF types and properties to identify how entities described by type sets are connected by property sets. We show that schema-level patterns can be aggregated and extracted from large Linked Data sets using efficient algorithms for mining frequent item sets. A subsequent visualisation of such patterns enables users to quickly understand which type of information is modelled on the Linked Data cloud and how this information is interconnected.
Status: VoR - Version of Record
Rights: Copyright © 2016 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.
URL: http://ceur-ws.org/Vol-1605/

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