A survey of joint intent detection and slot filling models in natural language understanding

H Weld, X Huang, S Long, J Poon, SC Han - ACM Computing Surveys, 2022‏ - dl.acm.org
Intent classification, to identify the speaker's intention, and slot filling, to label each token
with a semantic type, are critical tasks in natural language understanding. Traditionally the …

Automated machine learning approaches for emergency response and coordination via social media in the aftermath of a disaster: A review

L Dwarakanath, A Kamsin, RA Rasheed… - Ieee …, 2021‏ - ieeexplore.ieee.org
Social media communication serves as an integral part of the crisis response following a
mass emergency (disaster) event. Regardless of the kind of disaster event, whether it is a …

[HTML][HTML] Unveiling the dynamics of crisis events: Sentiment and emotion analysis via multi-task learning with attention mechanism and subject-based intent prediction

PYW Myint, SL Lo, Y Zhang - Information Processing & Management, 2024‏ - Elsevier
In the age of rapid internet expansion, social media platforms like Twitter have become
crucial for sharing information, expressing emotions, and revealing intentions during crisis …

Semi-dilated convolutional neural networks for epileptic seizure prediction

R Hussein, S Lee, R Ward, MJ McKeown - Neural Networks, 2021‏ - Elsevier
Epilepsy is a neurological brain disorder that affects∼ 75 million people worldwide.
Predicting epileptic seizures holds great potential for improving the quality of life of people …

Towards determining perceived audience intent for multimodal social media posts using the theory of reasoned action

T Mittal, S Chowdhury, P Guhan, S Chelluri… - Scientific Reports, 2024‏ - nature.com
Increasing use of social media has resulted in many detrimental effects in youth. With very
little control over multimodal content consumed on these platforms and the false narratives …

Modeling feedback in interaction with conversational agents—a review

A Axelsson, H Buschmeier, G Skantze - Frontiers in Computer Science, 2022‏ - frontiersin.org
Intelligent agents interacting with humans through conversation (such as a robot, embodied
conversational agent, or chatbot) need to receive feedback from the human to make sure …

[HTML][HTML] An explainable artificial intelligence approach for detecting empathy in textual communication

EC Montiel-Vázquez, JA Ramírez Uresti… - Applied Sciences, 2022‏ - mdpi.com
Empathy is a necessary component of human communication. However, it has been largely
ignored in favor of other concepts such as emotion and feeling in Affective computing …

Characterizing linguistic attributes for automatic classification of intent based racist/radicalized posts on tumblr micro-blogging website

S Agarwal, A Sureka - arxiv preprint arxiv:1701.04931, 2017‏ - arxiv.org
Research shows that many like-minded people use popular microblogging websites for
posting hateful speech against various religions and race. Automatic identification of racist …

[HTML][HTML] Mining textual and imagery instagram data during the COVID-19 pandemic

D Amanatidis, I Mylona, I Kamenidou, S Mamalis… - Applied Sciences, 2021‏ - mdpi.com
Instagram is perhaps the most rapidly gaining in popularity of photo and video sharing social
networking applications. It has been widely adopted by both end-users and organizations …

Multiple granularity user intention fairness recognition of intelligent government Q & A system via three-way decision

D Liang, Y Wu, W Duan - Information Sciences, 2023‏ - Elsevier
With respect to an intelligent government questions & answers (Q & A) system, user intention
recognition for government affairs is a key issue. Accurate intention recognition can …