Papers by Yoshiyasu Takefuji
Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia (2020.emnlp-demos)
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Ikuya Yamada, Akari Asai, Jin Sakuma, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji, Yuji Matsumoto
| Challenge: | Existing tools for learning the embeddings of words and entities from Wikipedia are not yet available. |
| Approach: | They propose a Python-based tool for learning Wikipedia embeddings from Wikipedia . they use a Wikipedia dump file as an argument to issue a single command . |
| Outcome: | The proposed tool achieves state-of-the-art results on the KORE entity relatedness dataset and competitive results on benchmark datasets. |
Representation Learning of Entities and Documents from Knowledge Base Descriptions (C18-1)
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| Challenge: | Using documents extracted from Wikipedia, we train a neural network model that learns distributed representations of entities and documents directly from a knowledge base. |
| Approach: | They propose a neural network model that learns distributed representations of entities from a knowledge base. |
| Outcome: | The proposed model performs state-of-the-art on fine-grained entity typing and multiclass text classification tasks. |