Abstract
A word is the smallest item in Natural Language Processing. However, there is no obvious boundary for Chinese words. How to segment Chinese words always obstructs Chinese researches and applications. Nowadays, a neural network model, Seq2Seq with LSTM, is well-known for translation or chatbot application. In this paper, we try to transform the Chinese word segmentation problem into a translation problem. And we utilized an open-source chatbot to simulate the translation task. In our experimental results, we can produce similar Chinese word segmentation results when we provide training data which is automatically generated from famous Chinese word segmentation services.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2019 3rd International Conference on Natural Language Processing and Information Retrieval, NLPIR 2019 |
| Publisher | Association for Computing Machinery |
| Pages | 20-24 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450362795 |
| DOIs | |
| State | Published - 28 06 2019 |
| Event | 3rd International Conference on Natural Language Processing and Information Retrieval, NLPIR 2019 - Tokushima, Japan Duration: 28 06 2019 → 30 06 2019 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 3rd International Conference on Natural Language Processing and Information Retrieval, NLPIR 2019 |
|---|---|
| Country/Territory | Japan |
| City | Tokushima |
| Period | 28/06/19 → 30/06/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computing Machinery.
Keywords
- Chatbot
- Chinese word segmentation
- LSTM
- Seq2Seq
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