Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Laiba Mehnaz"'
Autor:
Laiba Mehnaz, Debanjan Mahata, Rakesh Gosangi, Uma Sushmitha Gunturi, Riya Jain, Gauri Gupta, Amardeep Kumar, Isabelle G. Lee, Anish Acharya, Rajiv Ratn Shah
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77a7feea1540f1214704cad6a1071278
https://doi.org/10.18653/v1/2021.emnlp-main.499
https://doi.org/10.18653/v1/2021.emnlp-main.499
Autor:
Rajni Jindal, Laiba Mehnaz
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811582882
Drug mention detection in tweets is defined as a binary classification task that aims to distinguish tweets that mention a drug from those which do not. In our work, we aim to use transfer learning for automatic classification of tweets mentioning a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e648e2cba695bf4aff5d3b5e09b1a29f
https://doi.org/10.1007/978-981-15-8289-9_33
https://doi.org/10.1007/978-981-15-8289-9_33
Autor:
Kartik Aggarwal, Yaman Kumar, Haimin Zhang, Sarthak Anand, Karan Uppal, Laiba Mehnaz, Debanjan Mahata, Simra Shahid, Rajiv Ratn Shah
Publikováno v:
SemEval@NAACL-HLT
In this paper we present our approach to tackle the Suggestion Mining from Online Reviews and Forums Sub-Task A. Given a review, we are asked to predict whether the review consists of a suggestion or not. Our model is based on Universal Language Mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e55c05e3f05f99f8b69f441406f2fd3
https://doi.org/10.18653/v1/s19-2213
https://doi.org/10.18653/v1/s19-2213
Autor:
Sarthak Anand, Rajiv Ratn Shah, Haimin Zhang, Simra Shahid, Debanjan Mahata, Karan Uppal, Yaman Kumar, Laiba Mehnaz
Publikováno v:
SemEval@NAACL-HLT
In this paper we present our approach and the system description for Sub Task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media. Sub Task A involves identifying if a given tweet is offensive and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b997ddaa096c6b5f9c0ec1f1ff4fb17d
https://doi.org/10.18653/v1/s19-2122
https://doi.org/10.18653/v1/s19-2122
Autor:
Haimin Zhang, Yaman Kumar, Simra Shahid, Laiba Mehnaz, Rajiv Ratn Shah, Sarthak Anand, Debanjan Mahata
Publikováno v:
Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task.
In this paper, we present our approach and the system description for the Social Media Mining for Health Applications (SMM4H) Shared Task 1,2 and 4 (2019). Our main contribution is to show the effectiveness of Transfer Learning approaches like BERT a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab34b1c57d2cc37b90d3a3cddc2570f1
https://doi.org/10.18653/v1/w19-3223
https://doi.org/10.18653/v1/w19-3223
Publikováno v:
Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task.
Social media-based text mining in healthcare has received special attention in recent times due to the enhanced accessibility of social media sites like Twitter. The increasing trend of spreading important information in distress can help patients re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a511ae6e525b88e37970a87327da224
https://doi.org/10.18653/v1/w18-5907
https://doi.org/10.18653/v1/w18-5907