| 基于文档相关性等级区分优化的网页排序方法; Page Ranking Based on the Optimization of the Document's Relevance Class | |
| 余烨 ; 张东站 | |
| 2013-04-05 | |
| 关键词 | 网页排序 神经网络 样本对 搜索引擎 Page Ranking Back Propagation Pairwise Search Engine |
| 英文摘要 | 利用机器学习方法自动构建排序模型,在PAIrWISE方法上平等化每个查询,扩充训练集加大文档不同相关性等级间的区分度和减少不相关文档的噪声影响,利用交叉熵计算误差函数来提高排序算法的性能。在公开数据集lETOr 4.0上的实验结果显示该方法可以提高排序结果的准确率,证明本方法的有效性。; Uses the machine learning methods to automatically build a ranking model,just like the widely used Pairwise approach.Based on the Pairwise approach,the new approach is equal for each query.It uses the cross-entropy to calculation the loss and selects the Top N related documents to expand the training set to increase the document distinction and reduce the noise impact of the irrelevant documents so that can improve the performance of the ranking approach.Experimental studies were conducted using the LETOR 4.0 data set which improved the ranking accuracies and demonstrated the effectiveness of the proposed method. |
| 语种 | zh_CN |
| 内容类型 | 期刊论文 |
| 源URL | [http://dspace.xmu.edu.cn/handle/2288/127210]  |
| 专题 | 信息技术－已发表论文 |
| 推荐引用方式 GB/T 7714 | 余烨,张东站. 基于文档相关性等级区分优化的网页排序方法, Page Ranking Based on the Optimization of the Document's Relevance Class[J],2013. |
| APA | 余烨,&张东站.(2013).基于文档相关性等级区分优化的网页排序方法.. |
| MLA | 余烨,et al."基于文档相关性等级区分优化的网页排序方法".(2013). |
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