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Fine-grained Type Prediction of Entities using Knowledge Graph Embeddings

Sofronova, Radina

Abstract:
Wikipedia is the largest online encyclopedia, which appears in more than 301 different languages, with the English version containing more than 5.9 million articles. However, using Wikipedia means reading it and searching through pages to find the needed information. On the other hand, DBpedia contains the information of Wikipedia in a structured manner, that is easy to reuse. Knowledge bases such as DBpedia and Wikidata have been recognised as the foundation for diverse applications in the field of data mining, information retrieval and natural language processing. A knowledge base describes real-world objects and the interrelations between them as entities and properties. The entities that share common characteristics are associated with a corresponding type. One of the most important pieces of information in knowledge bases is the type of the entities described. However, it has been observed that type information is often noisy or incomplete. In general, there is a need for well-defined type information for the entities of a knowledge base. In this thesis, the task of fine-grained entity typing of entities of a knowledge base, more specifically - DBpedia, is addressed. ... mehr

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Volltext §
DOI: 10.5445/IR/1000100007
Veröffentlicht am 18.11.2019
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Hochschulschrift
Publikationsjahr 2019
Sprache Englisch
Identifikator KITopen-ID: 1000100007
Verlag KIT, Karlsruhe
Umfang ix, 46 S.
Art der Arbeit Abschlussarbeit - Bachelor
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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