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Adaptive Vocabulary Construction for Frustration Intensity Modelling in Customer Support Dialog Texts

, and . International Journal of Computer Science & Information Technology (IJCSIT), 12 (6): 01 - 15 (December 2020)
DOI: 10.5121/ijcsit.2020.12603

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Morphology-Inspired Word Segmentation for Neural Machine Translation., , and . DB&IS (Selected Papers), volume 315 of Frontiers in Artificial Intelligence and Applications, page 225-239. IOS Press, (2018)Adaptive Vocabulary Construction for Frustration Intensity Modelling in Customer Support, and . International Journal of Computer Science & Information Technology (IJCSIT), 12 (6): 01 - 15 (December 2020)Adaptive Vocabulary Construction for Frustration Intensity Modelling in Customer Support Dialog Texts, and . International Journal of Computer Science & Information Technology (IJCSIT), 12 (6): 01 - 15 (December 2020)Review of Non-English Corpora Annotated for Emotion Classification in Text.. DB&IS, volume 1243 of Communications in Computer and Information Science, page 96-108. Springer, (2020)Insights into archaeological human sample microbiome using 16S rRNA gene sequencing., , , , , , , , and . BIBM, page 2264-2266. IEEE Computer Society, (2017)Frustration Level in Customer Support Tweets: Towards a Language-Independent Model., and . Balt. J. Mod. Comput., (2022)Frustration Level Annotation in Latvian Tweets with Non-Lexical Means of Expression., and . RANLP, page 814-823. INCOMA Ltd., (2021)Frustration Level Analysis in Customer Support Tweets for Different Languages., and . Doctoral Consortium/Forum@DB&IS, volume 3158 of CEUR Workshop Proceedings, page 45-54. CEUR-WS.org, (2022)