Papers with aggregation learning function

1 papers
Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation (D19-1)

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Challenge: Currently, Chinese characters share glyph and phonetic variations to escape detection algorithms due to their complexity and complexity.
Approach: They propose a Chinese variation-enhanced Graph Embedding algorithm that can learn Chinese character embeddings and latent variation families.
Outcome: The proposed model outperforms state-of-the-art models on Chinese spam detection datasets and review datasets.

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