图 书 馆
雷夫兰克：选择最有帮助的书完全无监督的算法综述RevRank: a Fully Unsupervised Algorithm for Selecting the Most Helpful Book Reviews |
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| 课程网址: | http://videolectures.net/icwsm09_tsur_rr/ |
| 主讲教师: | Oren Tsur |
| 开课单位: | 哈佛大学 |
| 开课时间: | 2009-06-24 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present an algorithm for automatically ranking usergenerated book reviews according to review helpfulness. Given a collection of reviews, our REVRANK algorithm identifies a lexicon of dominant terms that constitutes the core of a virtual optimal review. This lexicon defines a feature vector representation. Reviews are then converted to this representation and ranked according to their distance from a ‘virtual core’ review vector. The algorithm is fully unsupervised and thus avoids costly and error-prone manual training annotations. Our experiments show that REVRANK clearly outperforms a baseline imitating the Amazon user vote review ranking system. |
| 关 键 词: | 自动排序算法; 特征向量; 排名系统 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-30：lxf |
| 阅读次数: | 46 |