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Article
Engineering, Biomedical
Cheng Liu et al.
Summary: Advances in high throughput experimental methods have led to the availability of diverse omic datasets in clinical analysis applications. Different types of omic data contribute to the understanding of disease progression. By integrating multiple omics data, the proposed View-aware Collaborative Learning (VaCoL) method can jointly boost the performance of survival prediction and subgroup identification.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Jintao Wen et al.
Summary: Multimodal data is crucial for enhanced emotion recognition in conversation, but effectively fusing different modal features to understand contextual information is challenging. This work proposes a Dynamic Interactive Multiview Memory Network (DIMMN) model, which integrates interaction information and mines crossmodal dynamic dependencies for emotion recognition. Experimental results show that DIMMN achieves better performance compared to state-of-the-art methods.
INFORMATION FUSION
(2023)
Article
Computer Science, Artificial Intelligence
Wei Li et al.
Summary: The paper introduces a new task called emotion-cause pair extraction in conversations (ECPEC), which aims to extract pairs of emotional utterances and corresponding cause utterances in conversations. The utterance-level ECPEC task is more challenging as the distance between emotion and cause utterances is greater. The experimental results on the proposed ConvECPE dataset demonstrate the feasibility of the ECPEC task and the effectiveness of the framework.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Geng Tu et al.
Summary: This article proposes a knowledge selection framework called SKSEC that incorporates sentiment emotion and context to improve emotion recognition in conversations. By eliminating and refining external knowledge, the performance of the model can be effectively enhanced.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Wei Li et al.
Summary: This paper presents a fast, compact, and parameter-efficient framework for conversational sentiment analysis, which outperforms the state of the art in most cases according to extensive experiments on three standard datasets.
Article
Engineering, Electrical & Electronic
Ke Zhang et al.
Summary: The ERLDK model proposed in this paper uses reinforcement learning and domain knowledge for multimodal emotion recognition in conversational videos, providing real-time capability. The model utilizes history utterances as emotion-pairs to recognize the context of the subsequent utterance. Experimental results demonstrate that ERLDK achieves state-of-the-art performance on weighted average and most specific emotion categories.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Songlong Xing et al.
Summary: This article proposes an Adapted Dynamic Memory Network (A-DMN) for Emotion Recognition in Conversation (ERC), which effectively synthesizes self and inter-speaker influences and obtains refined representations through multiple iterations. Additionally, the study explores cross-modal fusion in multimodal ERC and presents a convolution-based method that is efficient in extracting local interactions.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Xin He et al.
Summary: Deep learning techniques have achieved remarkable results in various tasks, but building a high-quality DL system requires human expertise. Automated machine learning is a promising solution that is currently being extensively researched.
KNOWLEDGE-BASED SYSTEMS
(2021)
Editorial Material
Computer Science, Artificial Intelligence
Amir Hussain et al.
INFORMATION FUSION
(2021)
Article
Computer Science, Artificial Intelligence
Duc-Anh Phan et al.
Summary: The paper proposes a semi-supervised multilabel method for predicting emotions from conversation transcripts, utilizing deep-learning autoencoder and word2vec to build an emotion lexicon. Experimental results suggest the method is effective and slightly behind human annotators.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Vasco Lopes et al.
Summary: Sentiment analysis is a research topic focused on analyzing data to extract information related to the sentiment it causes, with applications ranging from machine learning techniques trained on large corpora to the emergence of sentiment analysis in images. Despite recent advances, combining both image and textual information in social media data classification still faces challenges, mainly due to subjectivity, inter-class homogeneity and fusion data differences. Our proposed method achieves state-of-the-art performance in the B-T4SA dataset by combining textual and image sentiment analysis through AutoML with a random search for the best model.
2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
(2021)
Article
Chemistry, Multidisciplinary
Qingbiao Li et al.
APPLIED SCIENCES-BASEL
(2020)
Article
Computer Science, Artificial Intelligence
Yosephine Susanto et al.
IEEE INTELLIGENT SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Jie Zhou et al.
KNOWLEDGE-BASED SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Yukun Ma et al.
INFORMATION FUSION
(2020)
Editorial Material
Computer Science, Artificial Intelligence
Erik Cambria et al.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2019)
Article
Computer Science, Artificial Intelligence
Navonil Majumder et al.
IEEE INTELLIGENT SYSTEMS
(2019)
Article
Psychology, Multidisciplinary
Ankush Chatterjee et al.
COMPUTERS IN HUMAN BEHAVIOR
(2019)
Article
Computer Science, Artificial Intelligence
Murtadha Talib AL-Sharuee et al.
DATA & KNOWLEDGE ENGINEERING
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Soujanya Poria et al.
2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM)
(2017)
Article
Computer Science, Artificial Intelligence
Jun Zhang et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2007)
Article
Acoustics
CM Lee et al.
IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING
(2005)
