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End date: 2023 × Start date: 2020 × Has files: Yes × Version: publishedVersion × Subject: Knowledge Graph × Subject: Konferenzschrift ×

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Now showing 1 - 3 of 3
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    Improving Zero-Shot Text Classification with Graph-based Knowledge Representations
    (Aachen, Germany : RWTH Aachen, 2022) Hoppe, Fabian; Hartig, Olaf; Seneviratne, Oshani
    Insufficient training data is a key challenge for text classification. In particular, long-tail class distributions and emerging, new classes do not provide any training data for specific classes. Therefore, such a zeroshot setting must incorporate additional, external knowledge to enable transfer learning by connecting the external knowledge of previously unseen classes to texts. Recent zero-shot text classifier utilize only distributional semantics defined by large language models and based on class names or natural language descriptions. This implicit knowledge contains ambiguities, is not able to capture logical relations nor is it an efficient representation of factual knowledge. These drawbacks can be avoided by introducing explicit, external knowledge. Especially, knowledge graphs provide such explicit, unambiguous, and complementary, domain specific knowledge. Hence, this thesis explores graph-based knowledge as additional modality for zero-shot text classification. Besides a general investigation of this modality, the influence on the capabilities of dealing with domain shifts by including domain-specific knowledge is explored.
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    Diving into Knowledge Graphs for Patents: Open Challenges and Benefits
    (Aachen, Germany : RWTH Aachen, 2023) Dessi, Danilo; Dessi, Rima; Alam, Mehwish; Trojahn, Cassia; Hertling, Sven; Pesquita, Catia; Aebeloe, Christian; Aras, Hidir; Azzam, Amr; Cano, Juan; Domingue, John; Gottschalk, Simon; Hartig, Olaf; Hose, Katja; Kirrane, Sabrina; Lisena, Pasquale; Osborne, Francesco; Rohde, Philipp; Steels, Luc; Taelman, Ruben; Third, Aisling; Tiddi, Ilaria; Türker, Rima
    Textual documents are the means of sharing information and preserving knowledge for a large variety of domains. The patent domain is also using such a paradigm which is becoming difficult to maintain and is limiting the potentialities of using advanced AI systems for domain analysis. To overcome this issue, it is more and more frequent to find approaches to transform textual representations into Knowledge Graphs (KGs). In this position paper, we discuss KGs within the patent domain, present its challenges, and envision the benefits of such technologies for this domain. In addition, this paper provides insights of such KGs by reproducing an existing pipeline to create KGs and applying it to patents in the computer science domain.
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    Workshop on PIDs within NFDI: Report of the Working Group “Persistent Identifiers (PID)” of the Section Common Infrastructures of the NFDI
    (Zenodo, 2023) Arend, Daniel; Bach, Janete; Elger, Kirsten; Göller, Sandra; Hagemann-Wilholt, Stephanie; Krahl, Rolf; Lange, Matthias; Linke, David; Mayer, Desiree; Mutschke, Peter; Reimer, Lorenz; Scheidgen, Markus; Schrader, Antonia C.; Selzer, Michael; Wieder, Philipp
    In order to gain an overview of the current state of the discussion on PIDs and for the identification of use cases for the initiation phase of a PID service within the NFDI basic services, the working group Persistent Identifier of the Section Common Infrastructures of the NFDI hosted an online workshop in January 2023. In the course of the workshop, members of nine different NFDI consortia presented the current application of PIDs in their consortia.