A First Experiment on Including Text Literals in KGloVe
Cochez, M., Garofalo, M., Lenßen, J., & Pellegrino, M. A. (2018). A First Experiment on Including Text Literals in KGloVe. In K.-S. Choi, L. E. Anke, T. Declerck, D. Gromann, J.-D. Kim, A.-C. N. Ngomo, M. Saleem, & R. Usbeck (Eds.), SemDeep-4_NLIWOD-4 2018 : Joint Proceedings of ISWC 2018 Workshops SemDeep-4 and NLIWOD-4 (pp. 103-106). RWTH Aachen University. CEUR workshop proceedings, 2241. http://ceur-ws.org/Vol-2241/
Published inCEUR workshop proceedings
© the Authors, 2018.
Graph embedding models produce embedding vectors for entities and relations in Knowledge Graphs, often without taking literal properties into account. We show an initial idea based on the combination of global graph structure with additional information provided by textual information in properties. Our initial experiment shows that this approach might be useful, but does not clearly outperform earlier approaches when evaluated on machine learning tasks.
PublisherRWTH Aachen University
ConferenceWorkshop on Semantic Deep Learning
Is part of publicationSemDeep-4_NLIWOD-4 2018 : Joint Proceedings of ISWC 2018 Workshops SemDeep-4 and NLIWOD-4
Publication in research information system
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