方法证据记录
Multilingual Doc2Vec
Multilingual Doc2Vec extends the Paragraph Vector framework of Le and Mikolov (2014) to two or more languages, training document-level embeddings in a shared or aligned vector space so that semantically similar documents — regardless of their language — end up close together. It enables cross-lingual document retrieval, classification, and clustering without requiring parallel corpora or translation.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Multilingual Paragraph Vector (Doc2Vec) Model
分类方法记录 · ml-model / deep-learning
- Le, Q., & Mikolov, T. (2014). Distributed representations of sentences and documents. In Proceedings of the 31st International Conference on Machine Learning (ICML), PMLR 32(2), 1188–1196. · URL
- Multilingualism. Wikipedia. · URL
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