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A survey of joint intent detection and slot filling models in natural language understanding
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 …
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
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 …
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
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 …
crucial for sharing information, expressing emotions, and revealing intentions during crisis …
Semi-dilated convolutional neural networks for epileptic seizure prediction
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 …
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
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 …
little control over multimodal content consumed on these platforms and the false narratives …
Modeling feedback in interaction with conversational agents—a review
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 …
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
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 …
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
Research shows that many like-minded people use popular microblogging websites for
posting hateful speech against various religions and race. Automatic identification of racist …
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
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 …
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
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 …
recognition for government affairs is a key issue. Accurate intention recognition can …