Results 71 to 80 of about 15,528 (226)

Joint Extraction Method for Spatial Relations in Chinese Geological Texts

Earth and Space Science, Volume 12, Issue 8, August 2025.
Abstract Extracting spatial relations of geological entities is an important prerequisite for achieving natural language processing tasks such as geological knowledge question answering and semantic search, and is an important means to achieve structural reconstruction of unstructured geological data.
Chuan Chen, Xiuguo Liu, Weihua Hua, Xinling Zeng, Zihan Cao, Peng Li, Chunyu Qi, Yu Huang, Jiameng Chen, Wencheng Wei   +9 more
wiley   +1 more source

Complex Word Identification: Challenges in Data Annotation and System Performance

, 2017
This paper revisits the problem of complex word identification (CWI) following up the SemEval CWI shared task. We use ensemble classifiers to investigate how well computational methods can discriminate between complex and non-complex words.
Malmasi, Shervin, Paetzold, Gustavo, Specia, Lucia, Zampieri, Marcos   +3 more
core   +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

SemEval-2017 Task 12: Clinical TempEval [PDF]

Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), 2017
Clinical TempEval 2017 aimed to answer the question: how well do systems trained on annotated timelines for one medical condition (colon cancer) perform in predicting timelines on another medical condition (brain cancer)? Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal ...
Guergana Savova, James Pustejovsky, Martha Palmer, Steven Bethard   +3 more
openaire   +2 more sources

Multi-task transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection

Journal of Biomedical Semantics
Background The semantics of entities extracted from a clinical text can be dramatically altered by modifiers, including entity negation, uncertainty, conditionality, severity, and subject.
Abdullateef I. Almudaifer, Whitney Covington, JaMor Hairston, Zachary Deitch, Ankit Anand, Caleb M. Carroll, Estera Crisan, William Bradford, Lauren A. Walter, Ellen F. Eaton, Sue S. Feldman, John D. Osborne   +11 more
doaj   +1 more source

Aspect-Based Sentiment Analysis of Twitter Influencers to Predict the Trend of Cryptocurrencies Based on Hybrid Deep Transfer Learning Models

IEEE Access, 2023
With the expansion of social networks, sentiment analysis has become one of the hot topics in machine learning. However, in traditional sentiment analysis, the text is considered of a general nature and ignores the different aspects that may exist in the
Kia Jahanbin, Mohammad Ali Zare Chahooki
doaj   +1 more source

Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets

, 2017
There has been a good amount of progress in sentiment analysis over the past 10 years, including the proposal of new methods and the creation of benchmark datasets.
Barnes, Jeremy, Klinger, Roman, Walde, Sabine Schulte im   +2 more
core   +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

ADeCNN: An Improved Model for Aspect-Level Sentiment Analysis Based on Deformable CNN and Attention

IEEE Access, 2020
Aspect-level sentiment analysis aims at identifying the sentiment polarity of target in the context. In most of the previous sentiment analysis models, there usually exists the problem of insufficient extraction capability of local features and long ...
Jie Zhou, Siqi Jin, Xinli Huang
doaj   +1 more source

OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers using Piecewise Convolutional Neural Networks

, 2018
We describe our system for SemEval-2018 Shared Task on Semantic Relation Extraction and Classification in Scientific Papers where we focus on the Classification task.
Dhyani, Dushyanta
core   +1 more source