1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CL2020★ 1 cited
Hierarchical Multi Task Learning with Subword Contextual Embeddings for Languages with Rich Morphology
Arda Akdemir, Tetsuo Shibuya, Tunga Güngör
Morphological information is important for many sequence labeling tasks in Natural Language Processing (NLP). Yet, existing approaches rely heavily on manual annotations or externa…
cs.CL2020
Generating Word and Document Embeddings for Sentiment Analysis
Cem Rıfkı Aydın, Tunga Güngör, Ali Erkan
Sentiments of words differ from one corpus to another. Inducing general sentiment lexicons for languages and using them cannot, in general, produce meaningful results for different…