1 |
One model for the learning of language.
|
|
|
|
In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022)
|
|
BASE
|
|
Show details
|
|
2 |
Computational Measures of Deceptive Language: Prospects and Issues
|
|
|
|
In: ISSN: 2297-900X ; EISSN: 2297-900X ; Frontiers in Communication ; https://hal.archives-ouvertes.fr/hal-03629780 ; Frontiers in Communication, Frontiers, 2022, 7, pp.792378. ⟨10.3389/fcomm.2022.792378⟩ (2022)
|
|
BASE
|
|
Show details
|
|
3 |
Animal linguistics in the making: the Urgency Principle and titi monkeys’ alarm system
|
|
|
|
In: ISSN: 0394-9370 ; Ethology Ecology and Evolution ; https://hal.inrae.fr/hal-03518874 ; Ethology Ecology and Evolution, Taylor & Francis, 2022, pp.1-17. ⟨10.1080/03949370.2021.2015452⟩ (2022)
|
|
BASE
|
|
Show details
|
|
4 |
A Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
|
|
|
|
In: Journal of Open Humanities Data; Vol 8 (2022); 3 ; 2059-481X (2022)
|
|
BASE
|
|
Show details
|
|
6 |
German Climate Change Tweet Corpus (GerCCT) ...
|
|
|
|
Abstract:
First release of the GerCCT Corpus, a German tweet resource annotated for argument components, argument properties, sarcasm and toxic language. The corpus consists of 1,200 tweets and its annotations. Each tweet is associated with its respective source tweet, i.e. the tweet it replies to. Source tweets were used to provide annotators with additional context. The annotations refer to the reply tweet, i.e. NOT to the source tweet. For copyright reasons we cannot distribute the actual tweet content. Instead we share the source and reply tweet IDs and the annotations. The current version includes class annotations on the document level, i.e. on the tweet level. We are working on creating the respective span annotations. ...
|
|
Keyword:
argument mining; computational linguistics; German; Twitter
|
|
URL: https://zenodo.org/record/6479492 https://dx.doi.org/10.5281/zenodo.6479492
|
|
BASE
|
|
Hide details
|
|
7 |
Using Machine Learning for Pharmacovigilance: A Systematic Review
|
|
|
|
In: Pharmaceutics; Volume 14; Issue 2; Pages: 266 (2022)
|
|
BASE
|
|
Show details
|
|
8 |
Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
|
|
|
|
In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
|
|
BASE
|
|
Show details
|
|
11 |
Hebrew Transformed: Machine Translation of Hebrew Using the Transformer Architecture
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Causal and Semantic Relations in L2 Text Processing: An Eye-Tracking Study
|
|
Nahatame, Shingo. - : University of Hawaii National Foreign Language Resource Center, 2022. : Center for Language & Technology, 2022
|
|
BASE
|
|
Show details
|
|
13 |
Phylogenetic trees: Grammar versus vocabulary
|
|
|
|
In: Russian Journal of Linguistics, Vol 26, Iss 1, Pp 31-50 (2022) (2022)
|
|
BASE
|
|
Show details
|
|
14 |
French de and en as expressions of the genitive case: a unified analysis within LFG and computational implementation in XLE1
|
|
|
|
In: DELTA: Documentação e Estudos em Linguística Teórica e Aplicada; v. 37 n. 1 (2021) ; 1678-460X ; 0102-4450 (2022)
|
|
BASE
|
|
Show details
|
|
|
|