QQ客服 官方微博 反馈留言

	Efficiently collecting relevance information from clickthroughs for web retrieval system evaluation
	He, Jing ; Zhao, Wayne Xin ; Shu, Baihan ; Li, Xiaoming ; Yan, Hongfei
	2011
英文摘要	Various click models have been recently proposed as a principled approach to infer the relevance of documents from the clickthrough data. The inferred document relevance is potentially useful in evaluating the Web retrieval systems. In practice, it generally requires to acquire the accurate evaluation results within minimal users' query submissions. This problem is important for speeding up search engine development and evaluation cycle and acquiring reliable evaluation results on tail queries. In this paper, we propose a reordering framework for efficient evaluation problem in the context of clickthrough based Web retrieval evaluation. The main idea is to move up the documents that contribute more for the evaluation task. In this framework, we propose four intuitions and formulate them as an optimization problem. Both user study and TREC data based experiments validate that the reordering framework results in much fewer query submissions to get accurate evaluation results with only a little harm to the users' utility.; EI; 0
语种	英语
DOI标识	10.1145/2009916.2009956
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/295222]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	He, Jing,Zhao, Wayne Xin,Shu, Baihan,et al. Efficiently collecting relevance information from clickthroughs for web retrieval system evaluation. 2011-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。