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of 42
pro vyhledávání: '"Portisch, Jan"'
The entity type information in Knowledge Graphs (KGs) such as DBpedia, Freebase, etc. is often incomplete due to automated generation or human curation. Entity typing is the task of assigning or inferring the semantic type of an entity in a KG. This
Externí odkaz:
http://arxiv.org/abs/2207.14094
Autor:
Portisch, Jan, Paulheim, Heiko
Knowledge graph embedding is a representation learning technique that projects entities and relations in a knowledge graph to continuous vector spaces. Embeddings have gained a lot of uptake and have been heavily used in link prediction and other dow
Externí odkaz:
http://arxiv.org/abs/2207.06014
One of the strongest signals for automated matching of knowledge graphs and ontologies are textual concept descriptions. With the rise of transformer-based language models, text comparison based on meaning (rather than lexical features) is available
Externí odkaz:
http://arxiv.org/abs/2204.13931
Autor:
Portisch, Jan, Costa, Guilherme, Stefani, Karolin, Kreplin, Katharina, Hladik, Michael, Paulheim, Heiko
Ontology matching is a core task when creating interoperable and linked open datasets. In this paper, we explore a novel structure-based mapping approach which is based on knowledge graph embeddings: The ontologies to be matched are embedded, and an
Externí odkaz:
http://arxiv.org/abs/2204.04040
Autor:
Portisch, Jan, Paulheim, Heiko
RDF2vec is a knowledge graph embedding mechanism which first extracts sequences from knowledge graphs by performing random walks, then feeds those into the word embedding algorithm word2vec for computing vector representations for entities. In this p
Externí odkaz:
http://arxiv.org/abs/2204.02777
One of the strongest signals for automated matching of ontologies and knowledge graphs are the textual descriptions of the concepts. The methods that are typically applied (such as character- or token-based comparisons) are relatively simple, and the
Externí odkaz:
http://arxiv.org/abs/2109.07401
Autor:
Portisch, Jan, Paulheim, Heiko
The RDF2vec method for creating node embeddings on knowledge graphs is based on word2vec, which, in turn, is agnostic towards the position of context words. In this paper, we argue that this might be a shortcoming when training RDF2vec, and show that
Externí odkaz:
http://arxiv.org/abs/2108.05280
The use of external background knowledge can be beneficial for the task of matching schemas or ontologies automatically. In this paper, we exploit six general-purpose knowledge graphs as sources of background knowledge for the matching task. The back
Externí odkaz:
http://arxiv.org/abs/2107.00001
This paper presents the FinMatcher system and its results for the FinSim 2021 shared task which is co-located with the Workshop on Financial Technology on the Web (FinWeb) in conjunction with The Web Conference. The FinSim-2 shared task consists of a
Externí odkaz:
http://arxiv.org/abs/2103.01576
Autor:
Abbas, Nacira, Alghamdi, Kholoud, Alinam, Mortaza, Alloatti, Francesca, Amaral, Glenda, d'Amato, Claudia, Asprino, Luigi, Beno, Martin, Bensmann, Felix, Biswas, Russa, Cai, Ling, Capshaw, Riley, Carriero, Valentina Anita, Celino, Irene, Dadoun, Amine, De Giorgis, Stefano, Delva, Harm, Domingue, John, Dumontier, Michel, Emonet, Vincent, van Erp, Marieke, Arias, Paola Espinoza, Fallatah, Omaima, Ferrada, Sebastián, Ocaña, Marc Gallofré, Georgiou, Michalis, Gesese, Genet Asefa, Gillis-Webber, Frances, Giovannetti, Francesca, Buey, Marìa Granados, Harrando, Ismail, Heibi, Ivan, Horta, Vitor, Huber, Laurine, Igne, Federico, Jaradeh, Mohamad Yaser, Keshan, Neha, Koleva, Aneta, Koteich, Bilal, Kurniawan, Kabul, Liu, Mengya, Ma, Chuangtao, Maas, Lientje, Mansfield, Martin, Mariani, Fabio, Marzi, Eleonora, Mesbah, Sepideh, Mistry, Maheshkumar, Tirado, Alba Catalina Morales, Nguyen, Anna, Nguyen, Viet Bach, Oelen, Allard, Pasqual, Valentina, Paulheim, Heiko, Polleres, Axel, Porena, Margherita, Portisch, Jan, Presutti, Valentina, Pustu-Iren, Kader, Mendez, Ariam Rivas, Roshankish, Soheil, Rudolph, Sebastian, Sack, Harald, Sakor, Ahmad, Salas, Jaime, Schleider, Thomas, Shi, Meilin, Spinaci, Gianmarco, Sun, Chang, Tietz, Tabea, Dhouib, Molka Tounsi, Umbrico, Alessandro, Berg, Wouter van den, Xu, Weiqin
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingl
Externí odkaz:
http://arxiv.org/abs/2012.11936