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pro vyhledávání: '"Rabab Alkhalifa"'
Autor:
Rabab Alkhalifa, Iman Bilal, Hsuvas Borkakoty, Jose Camacho-Collados, Romain Deveaud, Alaa El-Ebshihy, Luis Espinosa-Anke, Gabriela Gonzalez-Saez, Petra Galuščáková, Lorraine Goeuriot, Elena Kochkina, Maria Liakata, Daniel Loureiro, Harish Tayyar Madabushi, Philippe Mulhem, Florina Piroi, Martin Popel, Christophe Servan, Arkaitz Zubiaga
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282409
ECIR 2023: Advances in Information Retrieval
European Conference on Information Retrieval
European Conference on Information Retrieval, Apr 2023, Dublin, Ireland. pp.499-505, ⟨10.1007/978-3-031-28241-6_58⟩
ECIR 2023: Advances in Information Retrieval
European Conference on Information Retrieval
European Conference on Information Retrieval, Apr 2023, Dublin, Ireland. pp.499-505, ⟨10.1007/978-3-031-28241-6_58⟩
International audience; In this paper, we describe the plans for the first LongEval CLEF 2023 shared task dedicated to evaluating the temporal persistence of Information Retrieval (IR) systems and Text Classifiers. The task is motivated by recent res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94f8c74f3d421c3f7797e204b8a0b800
https://doi.org/10.1007/978-3-031-28241-6_58
https://doi.org/10.1007/978-3-031-28241-6_58
Performance of text classification models tends to drop over time due to changes in data, which limits the lifetime of a pretrained model. Therefore an ability to predict a model's ability to persist over time can help design models that can be effec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::440df7516103e7a81ac93fa51017a5ce
http://arxiv.org/abs/2205.05435
http://arxiv.org/abs/2205.05435
Given the rapidly evolving nature of social media and people's views, word usage changes over time. Consequently, the performance of a classifier trained on old textual data can drop dramatically when tested on newer data. While research in stance cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed7adc395519b73cf4a290b99c8ab087
Autor:
Rabab Alkhalifa, Arkaitz Zubiaga
Social media platforms provide a goldmine for mining public opinion on issues of wide societal interest and impact. Opinion mining is a problem that can be operationalised by capturing and aggregating the stance of individual social media posts as su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::353e00e5f97cdb9cf404d4ce94f3fb75
Autor:
Arkaitz Zubiaga, Rabab Alkhalifa
Publikováno v:
EVALITA
This paper presents our submission to the SardiStance 2020 shared task, describing the architecture used for Task A and Task B. While our submission for Task A did not exceed the baseline, retraining our model using all the training tweets, showed pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::161d1c83b3e47aefe8e3d0c36b5e2daa
https://doi.org/10.4000/books.aaccademia.7114
https://doi.org/10.4000/books.aaccademia.7114