Design and Efficacy of a Data Lake Architecture for Multimodal Emotion Feature Extraction in Social Media
Yuanyuan Fan,
Xifeng Mi
Abstract:In the rapidly evolving landscape of social media, the demand for precise sentiment analysis (SA) on multimodal data has become increasingly pivotal. This paper introduces a sophisticated data lake architecture tailored for efficient multimodal emotion feature extraction, addressing the challenges posed by diverse data types. The proposed framework encompasses a robust storage solution and an innovative SA model, multilevel spatial attention fusion (MLSAF), adept at handling text and visual data concurrently. … Show more
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