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Bootstrapping Multilingual Metadata Extraction: A Showcase in Cyrillic
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An Impact Assessment of ESF Training Courses for Unemployed in the Province of Bolzano
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Artificial intelligence, ethics, and intergenerational responsibility
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An impact assessment of ESF training courses for unemployed in the Province of Bolzano
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"Für den Spracherwerb ist es wichtig, auf Lerngelegenheiten in der Umgebung zu stoßen"
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Deutschkenntnisse entwickeln sich bei Geflüchteten und anderen Neuzugewanderten ähnlich: Sprachkurse spielen wichtige Rolle
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The Impacts of a Prototypical Home Visiting Program on Child Skills
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Leveraging literals for knowledge graph embeddings
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In: ISSN: 1613-0073 (2021)
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Text Mining and Dimension Reduction Methods of Exploring Isomorphism in Corporate Communication
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In: Archives of Data Science, Series A (Online First), 7 (1), P09, 21 S. online ; ISSN: 2363-9881 (2021)
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Reputation Through Observation: Active Lurkers in an Online Community
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In: Archives of Data Science, Series A (Online First), 5 (1), A32, 17 S. online ; ISSN: 2363-9881 (2021)
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Charaterizing RDF graphs through graph-based measures - Framework and assessment
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In: Semantic Web, 12 (5), 789-812 ; ISSN: 1570-0844, 2210-4968 (2021)
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Abstract:
The topological structure of RDF graphs inherently differs from other types of graphs, like social graphs, due to the pervasive existence of hierarchical relations (TBox), which complement transversal relations (ABox). Graph measures capture such particularities through descriptive statistics. Besides the classical set of measures established in the field of network analysis, such as size and volume of the graph or the type of degree distribution of its vertices, there has been some effort to define measures that capture some of the aforementioned particularities RDF graphs adhere to. However, some of them are redundant, computationally expensive, and not meaningful enough to describe RDF graphs. In particular, it is not clear which of them are efficient metrics to capture specific distinguishing characteristics of datasets in different knowledge domains (e.g., Cross Domain vs. Linguistics). In this work, we address the problem of identifying a minimal set of measures that is efficient, essential (non-redundant), and meaningful. Based on 54 measures and a sample of 280 graphs of nine knowledge domains from the Linked Open Data Cloud, we identify an essential set of 13 measures, having the capacity to describe graphs concisely. These measures have the capacity to present the topological structures and differences of datasets in established knowledge domains.
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Keyword:
ddc:330; Economics; info:eu-repo/classification/ddc/330
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URL: https://publikationen.bibliothek.kit.edu/1000137478 https://publikationen.bibliothek.kit.edu/1000137478/126937226 https://doi.org/10.5445/IR/1000137478
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Dynamiken der Wirtschaft des Mittleren Reichs. Warengewinnung von Getreide, Kupfer und Türkis
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Coronagraben in Switzerland: Culture and social distancing in times of COVID-19
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Managing Refugee Protection Crises: Policy Lessons from Economics and Political Science
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