图 书 馆
从词嵌入到文档距离From Word Embeddings To Document Distances |
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| 课程网址: | http://videolectures.net/icml2015_kusner_document_distances/ |
| 主讲教师: | Matt J. Kusner |
| 开课单位: | 康奈尔大学 |
| 开课时间: | 2015-12-05 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present the Word Mover’s Distance (WMD), a novel distance function between text documents. Our work is based on recent results in word embeddings that learn semantically meaningful representations for words from local co-occurrences in sentences. The WMD distance measures the dissimilarity between two text documents as the minimum amount of distance that the embedded words of one document need to “travel” to reach the embedded words of another document. We show that this distance metric can be cast as an instance of the Earth Mover’s Distance, a well studied transportation problem for which several highly efficient solvers have been developed. Our metric has no hyperparameters and is straight-forward to implement. Further, we demonstrate on eight real world document classification data sets, in comparison with seven state-of-the-art baselines, that the WMD metric leads to unprecedented low k-nearest neighbor document classification error rates. |
| 关 键 词: | 词嵌入; 机器学习; 文档距离 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-12-25：wujk |
| 最后编审: | 2023-12-25：wujk |
| 阅读次数: | 9 |