言葉のもつ広がりを、モデルの学習に活かそう -one-hot to distribution in language modeling-Takahiro Kubo
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1. The document discusses various statistical and neural network-based models for representing words and modeling semantics, including LSI, PLSI, LDA, word2vec, and neural network language models. 2. These models represent words based on their distributional properties and contexts using techniques like matrix factorization, probabilistic modeling, and neural networks to learn vector representatio
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