Results 81 to 90 of about 15,528 (226)

Exploring Causal Learning Through Graph Neural Networks: An In‐Depth Review

WIREs Data Mining and Knowledge Discovery, Volume 15, Issue 2, June 2025.
Graphical abstract of the survey with a taxonomical approach to causal learning with graph neural networks. ABSTRACT In machine learning, exploring data correlations to predict outcomes is a fundamental task. Recognizing causal relationships embedded within data is pivotal for a comprehensive understanding of system dynamics, the significance of which ...
Simi Job, Xiaohui Tao, Taotao Cai, Haoran Xie, Lin Li, Qing Li, Jianming Yong   +6 more
wiley   +1 more source

CTSys at SemEval-2018 Task 3: Irony in Tweets [PDF]

Proceedings of The 12th International Workshop on Semantic Evaluation, 2018
L'objectif de cet article est de fournir une description d'un système construit comme notre participation à la tâche 3 de SemEval-2018 sur la détection de l'ironie dans les tweets en anglais. Ce système classe un tweet comme ironique ou non ironique grâce à une approche d'apprentissage supervisé.
Myan Sherif, Sherine Mamdouh, Wegdan Ghazi   +2 more
openaire   +2 more sources

A New Sentiment-Enhanced Word Embedding Method for Sentiment Analysis

Applied Sciences, 2022
Since some sentiment words have similar syntactic and semantic features in the corpus, existing pre-trained word embeddings always perform poorly in sentiment analysis tasks.
Qizhi Li, Xianyong Li, Yajun Du, Yongquan Fan, Xiaoliang Chen   +4 more
doaj   +1 more source

Arabic Short‐Text Dataset for Sentiment Analysis of Tourism and Leisure Events

Expert Systems, Volume 42, Issue 5, May 2025.
ABSTRACT The focus of this study is to present the detailed process of collecting a dataset of Arabic short‐text in the tourism context and annotating this dataset for the task of sentiment analysis using an automatic zero‐shot labelling technique utilising transformer‐based models.
Seham Basabain, Ahmed Al‐Dubai, Erik Cambria, Khalid Alomar, Amir Hussain   +4 more
wiley   +1 more source

SemEval-2010 task 7 [PDF]

Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions - DEW '09, 2009
In this paper, we describe the Argument Selection and Coercion task, currently in development for the SemEval-2 evaluation exercise scheduled for 2010. This task involves characterizing the type of compositional operation that exists between a predicate and the arguments it selects.
Anna Rumshisky, James Pustejovsky
openaire   +2 more sources

RPf-GCNs: reciprocal perspective driven fused GCNs for rumor detection on social media

Journal of Big Data
The earliest detection of rumors across social media is the need to the hour in present global village. User’s are seamlessly connected in an unstructured network leading to rapid flow of information.
Zafran Khan, Jeonghwan Gwak, Naima Iltaf, Witold Pedrycz, Moongu Jeon   +4 more
doaj   +1 more source

Enhanced Sentiment Intensity Regression Through LoRA Fine-Tuning on Llama 3

IEEE Access
Sentiment analysis and emotion detection are critical research areas in natural language processing (NLP), offering benefits to numerous downstream tasks.
Diefan Lin, Yi Wen, Weishi Wang, Yan Su
doaj   +1 more source

CompiLIG at SemEval-2017 Task 1: Cross-Language Plagiarism Detection Methods for Semantic Textual Similarity

, 2017
We present our submitted systems for Semantic Textual Similarity (STS) Track 4 at SemEval-2017. Given a pair of Spanish-English sentences, each system must estimate their semantic similarity by a score between 0 and 5.
Agnes, Frederic, Besacier, Laurent, Ferrero, Jeremy, Schwab, Didier   +3 more
core   +1 more source

Leveraging Unsupervised Task Adaptation and Semi‐Supervised Learning With Semantic‐Enriched Representations for Online Sexism Detection

Expert Systems, Volume 42, Issue 2, February 2025.
ABSTRACT Over the past decade, the proliferation of hateful and sexist content targeting women on social media has become a concerning issue, adversely affecting women's lives and freedom of expression. Previous efforts to detect online sexism have utilized monolingual ensemble transformers combined with data augmentation techniques that incorporate ...
Francisco Rodríguez‐Sánchez, Jorge Carrillo‐de‐Albornoz, Laura Plaza   +2 more
wiley   +1 more source

SemEval-2015 Task 9: CLIPEval Implicit Polarity of Events [PDF]

Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), 2015
Sentiment analysis tends to focus on the po- larity of words, combining their values to de- tect which portion of a text is opinionated. CLIPEval wants to promote a more holistic approach, looking at psychological researches that frame the connotations of words as the emotional values activated by them.
Russo Irene, Caselli Tommaso, Strapparava Carlo   +2 more
openaire   +4 more sources