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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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Abstract:
Nowadays, Knowledge Graphs (KGs) have become invaluable for various applications such as named entity recognition, entity linking, question answering. However, there is a huge computational and storage cost associated with these KG-based applications. Therefore, there arises the necessity of transforming the high dimensional KGs into low dimensional vector spaces, i.e., learning representations for the KGs. Since a KG represents facts in the form of interrelations between entities and also using attributes of entities, the semantics present in both forms should be preserved while transforming the KG into a vector space. Hence, the main focus of this thesis is to deal with the multimodality and multilinguality of literals when utilizing them for the representation learning of KGs. The other task is to extract benchmark datasets with a high level of difficulty for tasks such as link prediction and triple classification. These datasets could be used for evaluating both kind of KG Embeddings, those using literals and those which do not include literals.
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Keyword:
Benchmark Datasets; ddc:330; Economics; info:eu-repo/classification/ddc/330; Knowledge Graph Completion; Knowledge Graph Embedding; Link Prediction; Literals
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URL: https://publikationen.bibliothek.kit.edu/1000141527/137280809 https://publikationen.bibliothek.kit.edu/1000141527 https://doi.org/10.5445/IR/1000141527
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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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16 |
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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