Genre Classification
Genre classification aims to automatically categorize data (e.g., music, text, video) into predefined genres based on inherent characteristics. Current research focuses on developing robust models using various techniques, including deep learning architectures like transformers, recurrent neural networks (RNNs), and convolutional neural networks (CNNs), often incorporating multimodal data and addressing challenges like domain transfer and data scarcity. This field is significant for improving information retrieval, recommendation systems, and content understanding across diverse domains, impacting both scientific understanding of genre representation and practical applications in various industries.
Papers
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