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Bootstrapping Multilingual Metadata Extraction: A Showcase in Cyrillic
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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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Semantic entity enrichment by leveraging multilingual descriptions for link prediction
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In: ISSN: 1613-0073 (2020)
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Leveraging multilingual descriptions for link prediction: Initial experiments
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In: CEUR workshop proceedings, 2721, 84-88 ; ISSN: 1613-0073 (2020)
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Deadline analysis of workflow graphs and workflow performance optimization
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Exploring Crosslingual Word Embeddings for Semantic Classification in Text and Dialogue
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Exploiting Knowledge Bases for Multilingual and Cross-lingual Semantic Annotation and Search
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Wikipedia infobox type prediction using embeddings
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In: ISSN: 1613-0073 (2018)
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Semantic Annotation and Search: Bridging the Gap between Text, Knowledge and Language
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Predicting wikipedia infobox type information using word embeddings on categories
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In: ISSN: 1613-0073 (2018)
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The Impact of Cryptocurrencies on the Internet of Things - Insights from Prototypes
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Managerial Cognition, Search and Strategy: Essays on Microfoundations
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The Semantic Multilingual Glossary of Mathematics (SMGloM) project or why do we need a semantic glossary of mathematics
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In: Archives of Data Science, Series A (Online First), 2 (1), 16 S. online ; ISSN: 2363-9881 (2017)
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Methods and Tools for Management of Distributed Event Processing Applications
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The causal impact of common native language on international trade: Evidence from a spatial regression discontinuity design: evidence from a spatial regression discontinuity design ...
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