Publication
Proceedings of the 2nd Workshop on Semantic Deep Learning (SemDeep - 2)
Dagmar Gromann; Thierry Declerck; Georg Heigold (Hrsg.)
Workshop on Semantic Deep Learning (SemDeep-2017), located at 12th International Conference on Computational Semantics (IWCS 2017), September 19, Montpellier, France, ACL, 9/2017.
Abstract
This interdisciplinary workshop aims to bring together Semantic Web and Deep Learning practitioners. Deep Learning (DL) is a set of machine learning algorithms that acquire data features and representations by submitting data to possibly multi-layered neural networks. Semantic Web (SW) technologies focus on structuring data to form machine-readable conceptual models and knowledge resources. Both fields have considerably impacted data analysis and representation. We believe that the integration of SW technologies and resources with DL methods is very promising for the exploration of natural language semantics. We thus invite submissions that illustrate how Semantic Web technologies and resources can benefit from Deep Learning or build on Deep Learning results. At the same time, we are interested in submissions that show how Semantic Web technologies and resources can assist in DL tasks.
Projekte
DEEPLEE - Tiefes Lernen für End-to-End-Anwendungen in der Sprachtechnologie,
QT21 - QT21: Quality Translation 21
QT21 - QT21: Quality Translation 21