图 书 馆
使用结构SVM预测不同子集Predicting Diverse Subsets Using Structural SVMs |
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| 课程网址: | http://videolectures.net/icml08_yue_pds/ |
| 主讲教师: | Yisong Yue |
| 开课单位: | 加州理工学院 |
| 开课时间: | 2008-08-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In many retrieval tasks, one important goal involves retrieving a diverse set of results (e.g., documents covering a wide range of topics for a search query). First of all, this reduces redundancy, effectively presenting more information with the presented results. Secondly, search queries are often ambiguous at some level. For example, the query “Jaguar” can refer to many different topics (such as the car or the feline). A set of documents with high topic diversity ensures that fewer users abandon the query because none of the results are relevant to them. Unlike existing approaches to learning retrieval functions, we present a method that explicitly trains to diversify results. In particular, we formulate the learning problem of predicting a diverse subset and derive a training algorithm based on structural SVMs. |
| 关 键 词: | 搜索查询; 检索功能; 训练算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-21：lxf |
| 阅读次数: | 34 |