本项目介绍了不同的句向量生成方法,主要分为以下内容:
*探索不同的生成句向量方法对问题匹配的影响
*探索不同的搜索策略的搜索精度和效率
*基于sentence-bert 生成句向量的方法
*评估sentence-bert生成句向量的方法
*基于esim的文本匹配方法.
*目前仍在进一步完善当中
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This project shows some sentence embedding method for FQA, including bert, word2vec and so on.
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- Python 64.4%
- Jupyter Notebook 35.6%