( en | de | ru )

 

Disambiguation of "Perera, Amal Shehan"

Author of the publication

copydeleteadd this publication to your clipboard
Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting.

, , , and . PACLIC, page 252-260. Association for Computational Linguistics, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Basher Shehan

Domenico Amalfitano

Linda Amalou-Döpke

Sarah Perera

Arshan Perera

 

Other publications of authors with the same name

User Localization Based on Call Detail Record., , , , and . IDEAL (1), volume 11871 of Lecture Notes in Computer Science, page 411-423. Springer, (2019)Evolutionary Nearest Neighbour Classification Framework., , and . SEDE, page 250-255. ISCA, (2009)SigmaLaw-ABSA: Dataset for Aspect-Based Sentiment Analysis in Legal Opinion Texts., , , , , , and . ICIIS, page 488-493. IEEE, (2020)Identifying Legal Party Members from Legal Opinion Documents using Natural Language Processing., , , , and . iiWAS, page 259-266. ACM, (2021)Shift-of-Perspective Identification within Legal Cases., , , , , and . ASAIL@ICAIL, volume 2385 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning., , , , , and . WASSA@EMNLP, page 260-265. Association for Computational Linguistics, (2018)SigmaLaw PBSA - A Deep Learning Approach For Aspect Based Sentiment Analysis in Legal Opinion Texts., , , , , and . J. Data Intell., 3 (1): 101-115 (2022)A Map Matching Algorithm for Noisy, Low Frequent Public Transportation GPS Data., and . CoDIT, page 1081-1086. IEEE, (2020)Heterogeneous data fusion with multiple kernel growing self organizing maps., , , , , , and . SCAI, volume 278 of Frontiers in Artificial Intelligence and Applications, page 167-176. IOS Press, (2015)Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting., , , and . PACLIC, page 252-260. Association for Computational Linguistics, (2020)