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A comprehensive survey on fake review detection, analyzing methods from traditional ML to LLM-based approaches, with a focus on information fusion and benchmark trends.
Proposes an entity alignment method for science and technology patents using graph convolution networks and BERT to fuse structural and attribute information, achieving better performance on benchmark datasets.
This systematic review of 139 studies proposes a unified framework and meta-analysis for document classification via multimodal and multiview information fusion, finding that fusion improves accuracy (mean gain of +5.28 percentage points) but highlights reproducibility challenges.
This paper proposes a novel evidential information fusion framework based on a reversible transformation between belief functions and possibilistic structure, using triangular norms for flexible combination beyond Dempster's rule.