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Predicting Emotional Word Ratings using Distributional Representations and Signed Clustering.

, , and . EACL (2), page 564-571. Association for Computational Linguistics, (2017)

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Dr. -Ing. Daniel Holder University of Stuttgart

Anpassbare Mensch-Maschine-Schnittstellen zwischen Adaptivität und Individualisierung, , , , and . Stuttgarter Symposium für Produktentwicklung SSP 2023 : Tagungsband zur Konferenz, Stuttgart, 25. Mai 2023, page 524-535. Stuttgart, Fraunhofer IAO, (2023)

Daniel Kempf University of Stuttgart

GALÆXI Scaling, , , , , , , , and . Dataset, (2024)Related to: Kempf, Daniel et al. “GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems.” (2024). arXiv: 2404.12703.
GALÆXI Scaling, , , , , , , , and . Dataset, (2024)Related to: Kempf, Daniel et al. “GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems.” (2024). arXiv: 2404.12703.GALÆXI Verification: Convergence Tests, , , , , , , , and . Dataset, (2024)Related to: Kempf, Daniel et al. “GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems.” (2024). arXiv: 2404.12703.GALÆXI Validation: Taylor-Green Vortex, , , , , , , , and . Dataset, (2024)Related to: Kempf, Daniel et al. “GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems.” (2024). arXiv: 2404.12703.
 

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Unsupervised word sense disambiguation with N-gram features., and . Artif. Intell. Rev., 41 (2): 241-260 (2014)The Remarkable Benefit of User-Level Aggregation for Lexical-based Population-Level Predictions., , , , , and . EMNLP, page 1167-1172. Association for Computational Linguistics, (2018)Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection., , , and . LREC, European Language Resources Association (ELRA), (2016)Where's @wally?: a classification approach to geolocating users based on their social ties., , , and . HT, page 11-20. ACM, (2013)Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective., , , and . PeerJ Computer Science, (2016)Expressively vulgar: The socio-dynamics of vulgarity and its effects on sentiment analysis in social media., , , and . COLING, page 2927-2938. Association for Computational Linguistics, (2018)Controlling Human Perception of Basic User Traits., , and . EMNLP, page 2335-2341. Association for Computational Linguistics, (2017)Exploring Stylistic Variation with Age and Income on Twitter., , and . ACL (2), The Association for Computer Linguistics, (2016)Categorizing and Inferring the Relationship between the Text and Image of Twitter Posts., and . ACL (1), page 2830-2840. Association for Computational Linguistics, (2019)Beyond Binary Labels: Political Ideology Prediction of Twitter Users., , , and . ACL (1), page 729-740. Association for Computational Linguistics, (2017)