Machine learningDeep learning / NLP / CV
多模态命名实体识别
多模态命名实体识别（Multimodal Named Entity Recognition, MNER）通过融合文本序列和互补模态（最常见的是图像）来扩展经典的命名实体识别（NER），以提高对人名、组织机构名、地名等命名实体的识别和分类能力，尤其是在视觉上下文能够消除歧义或弥补文本稀疏性的场景下。
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Method map
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来源
- Moon, S., Neves, L., & Carvalho, V. (2018). Multimodal Named Entity Recognition for Short Social Media Posts. Proceedings of NAACL-HLT 2018, pp. 852–860. Association for Computational Linguistics. link ↗
- Lu, D., Neves, L., Carvalho, V., Zhang, N., & Ji, H. (2018). Visual Attention Model for Name Tagging in Multimodal Social Media. Proceedings of ACL 2018, pp. 1990–1999. Association for Computational Linguistics. link ↗
如何引用本页
ScholarGate. (2026, June 3). Multimodal Named Entity Recognition (Text + Visual/Auxiliary Modality NER). ScholarGate. https://scholargate.app/zh/deep-learning/multimodal-named-entity-recognition
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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