...摘要: 排序是信息检索中的一个重要的环节,当今已经提出百余种用于构建排序函数的特征,如何利用这些特征构建更有效的排序函数成为当今的一个热点问题,因此排序学习(learning to rank)作为信息检索与机器学习的交叉学科,越来越受到人们的重视.根据不同的原则,查询可以分为不同的类别.
基于260个网页-相关网页
... 智能游走模型(Intelligent Surfer Model) 机器学习排序(Learning to Rank) 文档对方法(PairWise Approach) ...
基于194个网页-相关网页
以上来源于: WordNet
Workers of every rank are told these days that wide-ranging curiosity and continuous learning are vital to thriving in the modern economy.
如今,各个等级的员工都被告知,广泛的好奇心和持续的学习对在现代经济中蓬勃发展至关重要。
Making decisions about where to apply to college means learning more than rank, location, and who you know who went there.
做决定于选择哪里上学意味着知识大于排名,地理位置,你认识谁或谁去过那里。
The system performance has been greatly improved when the Log-linear and Rank-SVM models in machine learning are applied to fuse a few systems to get the last results list.
为了提高系统性能,应用机器学习中的Log - linear和Rank - SVM模型提出了基于系统融合的结果链表二次调序方法。
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