… Particularly, the multi-modal topic model is sequentially updated at each epoch using the
newly obtained event documents and the parameters of the previous epoch. In this situation, …

… -pivot (document features), probabilistic models, and frequent pattern matching [6], [7], [8],
[44]. Hence, we will list some common approaches for topic modeling used in event detection. …

… to classify multiclass social event directly. Qian et al. [98] also proposed a novel multi-modal
event topic model (mmETM), which can effectively model social media information such as …

… , multi-modal feature fusion methods based on topic models … Blei and Jordan [4] proposed
the Corr-LDA model to capture … ], this topic model is used to model multi-modal social event …

… In this article, we propose a multimodal supervised topic model based on semantic weighting
(Sem-… on the classification of multimodal social events, but there are few multimodal social …

… OVERALL FRAMEWORK We introduce a novel multi-modal topic memory network (MTMN) …
By employing a multi-modal blended attention network for multi-modal fusion, our model can …

… where we analyze the new event of a crisis with a model trained on previous crisis events.
First… MMBT [31]: recently proposed supervised multimodal bitransformers model for classifying …

… post and may affect the accuracy of event detection. In this work, we propose to focus attention
across multiple images for multimodal event detection, which is also more reasonable for …

… The main contribution of this study is the design and evaluation of a multi-modal Generative
Adversarial Network (mmGAN) for the traffic event detection and classification. The …

… ignore the existence of multimodal data in social media and only use … the multimodal
self-attentive feature fusion module, and MRNN_M denote MRDN without the contrary latent topic …