Results 71 to 80 of about 3,813 (211)

Query-Based Keyphrase Extraction from Long Documents

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022
Transformer-based architectures in natural language processing force input size limits that can be problematic when long documents need to be processed. This paper overcomes this issue for keyphrase extraction by chunking the long documents while keeping
Martin Dočekal, Pavel Smrž
doaj   +1 more source

Toxic Discourse in the Digital Battlefield: Analysing Telegram Channels During the Russia–Ukraine ‘Conflict’

Expert Systems, Volume 42, Issue 7, July 2025.
ABSTRACT Instant messenger Telegram has emerged as a favoured platform for far‐right activism, conspiracy theories, political propaganda, and misinformation, which has its own target audience. This study explores the application of multilingual pre‐trained language models to detect and measure toxicity in political content on Telegram channels.
Arsenii Tretiakov, Sergio D'Antonio‐Maceiras, Áurea Anguera de Sojo Hernández, Alejandro Martín   +3 more
wiley   +1 more source

Extracting knowledge from customer reviews: an integrated framework for digital platform analytics

International Transactions in Operational Research, Volume 32, Issue 4, Page 2061-2086, July 2025.
Abstract Online review sites play a crucial role in shaping consumer purchasing decisions, making the analysis of customer feedback essential for businesses. Given the complexity of these reviews, often including both quantitative and qualitative data, advanced analytical frameworks are necessary.
Anastasios Kyriakidis, Stelios Tsafarakis   +1 more
wiley   +1 more source

SemEval-2016 Task 12: Clinical TempEval [PDF]

Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), 2016
Clinical TempEval 2016 evaluated temporal information extraction systems on the clinical domain. Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal relation identification. Participant systems were trained and evaluated on a corpus of clinical and pathology notes from the Mayo
Steven Bethard, Guergana Savova, Wei-Te Chen, Leon Derczynski, James Pustejovsky, Marc Verhagen   +5 more
openaire   +1 more source

Modern Approaches to Aspect-Based Sentiment Analysis

Труды Института системного программирования РАН, 2018
The paper presents a survey of methods solving the actual task of aspect-based sentiment analysis. Solutions for this task were proposed at multiple natural language processing conferences.
I. . Andrianov, V. . Mayorov, D. . Turdakov   +2 more
doaj   +1 more source

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

What Matters in Irony Detection: An Extended Feature Engineering for Irony Detection in English Tweets.

Proceedings of the International Florida Artificial Intelligence Research Society Conference
In recent years, large-scale language models (LLMs) have nearly become the dominant force in almost every natural language processing (NLP) task. The primary research approach has focused on selecting the most appropriate language model for specific NLP ...
Linrui Zhang, Qixiang Pang, Belinda Copus   +2 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-2023 Task 6: LegalEval - Understanding Legal Texts

Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), 2023
In populous countries, pending legal cases have been growing exponentially. There is a need for developing NLP-based techniques for processing and automatically understanding legal documents. To promote research in the area of Legal NLP we organized the shared task LegalEval - Understanding Legal Texts at SemEval 2023.
Modi, Ashutosh, Kalamkar, Prathamesh, Karn, Saurabh, Tiwari, Aman, Joshi, Abhinav, Tanikella, Sai Kiran, Guha, Shouvik Kumar, Malhan, Sachin, Raghavan, Vivek   +8 more
openaire   +2 more sources

ShotgunWSD 2.0: An Improved Algorithm for Global Word Sense Disambiguation

IEEE Access, 2019
ShotgunWSD is a recent unsupervised and knowledge-based algorithm for global word sense disambiguation (WSD). The algorithm is inspired by the Shotgun sequencing technique, which is a broadly-used whole genome sequencing approach. ShotgunWSD performs WSD
Andrei M. Butnaru, Radu Tudor Ionescu
doaj   +1 more source