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Datenbanken und Informationssysteme (DBIS)

https://dl.gi.de/handle/20.500.12116/6252

Zu diesem Fachbereich gehört auch die Tagung Modellierung, organisiert vom Querschnitts-Fachausschuss Modellierung.

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Auflistung nach:

Auflistung Datenbanken und Informationssysteme (DBIS) nach Autor:in "Abedjan, Ziawasch"

1 - 2 von 2
  • Zeitschriftenartikel
    Improving RDF Data Through Association Rule Mining
    (Datenbank-Spektrum: Vol. 13, No. 2, 2013) Abedjan, Ziawasch; Naumann, Felix
    Linked Open Data comprises very many and often large public data sets, which are mostly presented in the Rdf triple structure of subject, predicate, and object. However, the heterogeneity of available open data requires significant integration steps before it can be used in applications. A promising and novel technique to explore such data is the use of association rule mining. We introduce “mining configurations”, which allow us to mine Rdf data sets in various ways. Different configurations enable us to identify schema and value dependencies that in combination result in interesting use cases. We present rule-based approaches for predicate suggestion, data enrichment, ontology improvement, and query relaxation. On the one hand we prevent inconsistencies in the data through predicate suggestion, enrichment with missing facts, and alignment of the corresponding ontology. On the other hand we support users to handle inconsistencies during query formulation through predicate expansion techniques. Based on these approaches, we show that association rule mining benefits the integration and usability of Rdf data.
  • Zeitschriftenartikel
    Particulate Matter Matters—The Data Science Challenge @ BTW 2019
    (Datenbank-Spektrum: Vol. 19, No. 3, 2019) Meyer, Holger J.; Grunert, Hannes; Waizenegger, Tim; Woltmann, Lucas; Hartmann, Claudio; Lehner, Wolfgang; Esmailoghli, Mahdi; Redyuk, Sergey; Martinez, Ricardo; Abedjan, Ziawasch; Ziehn, Ariane; Rabl, Tilmann; Markl, Volker; Schmitz, Christian; Serai, Dhiren Devinder; Gava, Tatiane Escobar
    For the second time, the Data Science Challenge took place as part of the 18th symposium “Database Systems for Business, Technology and Web” (BTW) of the Gesellschaft für Informatik (GI). The Challenge was organized by the University of Rostock and sponsored by IBM and SAP. This year, the integration, analysis and visualization around the topic of particulate matter pollution was the focus of the challenge. After a preselection round, the accepted participants had one month to adapt their developed approach to a substantiated problem, the real challenge. The final presentation took place at BTW 2019 in front of the prize jury and the attending audience. In this article, we give a brief overview of the schedule and the organization of the Data Science Challenge. In addition, the problem to be solved and its solution will be presented by the participants.