图 书 馆
命名实体识别的一个字表示的初步评价A Preliminary Evaluation of Word Representations for Named-Entity Recognition |
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| 课程网址: | http://videolectures.net/nipsworkshops09_turian_pewrner/ |
| 主讲教师: | Joseph Turian |
| 开课单位: | 蒙特利尔大学 |
| 开课时间: | 2010-01-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We use different word representations as word features for a named-entity recognition (NER) system with a linear model. This work is part of a larger empirical survey, evaluating different word representations on different NLP tasks. We evaluate Brown clusters, Collobert and Weston (2008) embeddings, and HLBL (Mnih & Hinton, 2009) embeddings of words. All three representations improve accuracy on NER, with the Brown clusters providing a larger improvement than the two embeddings, and the HLBL embeddings more than the Collobert and Weston (2008) embeddings. We also discuss some of the practical issues in using embeddings as features. Brown clusters are simpler than embeddings because they require less hyperparameter tuning. |
| 关 键 词: | 线性模型; 布朗集群; 超参数调整 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-02：毛岱琦(课程编辑志愿者) |
| 阅读次数: | 39 |