Results 21 to 30 of about 42,654 (268)

Persian Causality Corpus (PerCause) and the Causality Detection Benchmark

Iranian Journal of Information Processing & Management, 2022
Recognizing causal elements and causal relations in the text is among the challenging issues in natural language processing (NLP), specifically in low-resource languages such as Persian. In this research, we prepare a causality human-annotated corpus for
Zeinab Rahimi, Mehrnoush ShamsFard
doaj  

Large Scale Linguistic Processing of Tweets to Understand Social Interactions among Speakers of Less Resourced Languages: The Basque Case

Information, 2019
Social networks like Twitter are increasingly important in the creation of new ways of communication. They have also become useful tools for social and linguistic research due to the massive amounts of public textual data available.
Joseba Fernandez de Landa, Rodrigo Agerri, Iñaki Alegria   +2 more
doaj   +1 more source

Cross-Lingual Bimodal Emotion Recognition with LLM-Based Label Smoothing

Big Data and Cognitive Computing
Bimodal emotion recognition based on audio and text is widely adopted in video-constrained real-world applications such as call centers and voice assistants.
Elena Ryumina, Alexandr Axyonov, Timur Abdulkadirov, Darya Koryakovskaya, Dmitry Ryumin   +4 more
doaj   +1 more source

SSL-MEPR: A Semi-Supervised Multi-Task Cross-Domain Learning Framework for Multimodal Emotion and Personality Recognition

Machine Learning and Knowledge Extraction
The growing demand for personalized human–computer interaction calls for methods that jointly model emotional states and personality traits. However, large-scale multimodal corpora annotated for both tasks are still lacking.
Elena Ryumina, Alexandr Axyonov, Darya Koryakovskaya, Timur Abdulkadirov, Angelina Egorova, Sergey Fedchin, Alexander Zaburdaev, Dmitry Ryumin   +7 more
doaj   +1 more source

Multimodal Sequential Fashion Attribute Prediction

Information, 2019
We address multimodal product attribute prediction of fashion items based on product images and titles. The product attributes, such as type, sub-type, cut or fit, are in a chain format, with previous attribute values constraining the values of the next ...
Hasan Sait Arslan, Kairit Sirts, Mark Fishel, Gholamreza Anbarjafari   +3 more
doaj   +1 more source

Sentiment Analysis of the Top 5 E-commerce Platforms in Indonesia using Text Mining and Natural Language Processing (NLP)

Journal of Applied Informatics and Computing, 2023
This research attempts to depict a sentiment comparison of the top 5 E-commerce platforms in Indonesia by gathering the emotional tone behind sentence contents related to customer sentiments, customer experiences, and the brand reputation of E-commerce ...
R. A. E. Virgana Targa Sapanji, Dani Hamdani, Parlindungan Harahap   +2 more
doaj   +1 more source

On the definition of toxicity in NLP

CoRR, 2023
The fundamental problem in toxicity detection task lies in the fact that the toxicity is ill-defined. This causes us to rely on subjective and vague data in models' training, which results in non-robust and non-accurate results: garbage in - garbage out.
Sergey Berezin, Reza Farahbakhsh, Noël Crespi   +2 more
openaire   +2 more sources

Modern Approaches to Detect and Classify Comment Toxicity Using Neural Networks

Моделирование и анализ информационных систем, 2020
The growth of popularity of online platforms which allow users to communicate with each other, share opinions about various events, and leave comments boosted the development of natural language processing algorithms. Tens of millions of messages per day
Sergey V. Morzhov
doaj   +1 more source

Advanced Sarcasm Detection Using Transformer-Based Models: Analyzing Variations in Formal and Informal Languages

Applied Computational Intelligence and Soft Computing
Detecting sarcasm in text is notoriously difficult because it depends on subtle contextual cues that vary widely between communication styles. Informal language, such as satirical headlines, often signals sarcasm through exaggeration or playful wording ...
Mohammad Aman Ullah, Rebeka Sultana, Sadia Hasan Chowdhury, Farjana Akter Laila   +3 more
doaj   +1 more source

Reproducibility dataset for a large experimental survey on word embeddings and ontology-based methods for word similarity

Data in Brief, 2019
This data article introduces a reproducibility dataset with the aim of allowing the exact replication of all experiments, results and data tables introduced in our companion paper (Lastra-Díaz et al., 2019), which introduces the largest experimental ...
Juan J. Lastra-Díaz, Josu Goikoetxea, Mohamed Ali Hadj Taieb, Ana García-Serrano, Mohamed Ben Aouicha, Eneko Agirre   +5 more
doaj   +1 more source