Recency ranking by diversification of result set

Andrey Styskin, Fedor Romanenko, F. Vorobyev, P. Serdyukov
{"title":"Recency ranking by diversification of result set","authors":"Andrey Styskin, Fedor Romanenko, F. Vorobyev, P. Serdyukov","doi":"10.1145/2063576.2063862","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a web search retrieval approach which automatically detects recency sensitive queries and increases the freshness of the ordinary document ranking by a degree proportional to the probability of the need in recent content. We propose to solve the recency ranking problem by using result diversification principles and deal with the query's non-topical ambiguity appearing when the need in recent content can be detected only with uncertainty. Our offine and online experiments with millions of queries from real search engine users demonstrate the significant increase in satisfaction of users presented with a search result generated by our approach.","PeriodicalId":74507,"journal":{"name":"Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management","volume":"25 1","pages":"1949-1952"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2063576.2063862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

Abstract

In this paper, we propose a web search retrieval approach which automatically detects recency sensitive queries and increases the freshness of the ordinary document ranking by a degree proportional to the probability of the need in recent content. We propose to solve the recency ranking problem by using result diversification principles and deal with the query's non-topical ambiguity appearing when the need in recent content can be detected only with uncertainty. Our offine and online experiments with millions of queries from real search engine users demonstrate the significant increase in satisfaction of users presented with a search result generated by our approach.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于结果集多样化的近期排序
在本文中,我们提出了一种自动检测最近敏感查询的web搜索检索方法,并以与最近内容中需要的概率成比例的程度增加普通文档的新鲜度排名。我们提出利用结果多样化原则来解决最近排序问题,并处理仅通过不确定性就可以检测到最近内容中的需求时出现的查询的非主题歧义。我们对来自真实搜索引擎用户的数百万查询进行的离线和在线实验表明,通过我们的方法生成的搜索结果显著提高了用户的满意度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
scACT: Accurate Cross-modality Translation via Cycle-consistent Training from Unpaired Single-cell Data. iMIRACLE: an Iterative Multi-View Graph Neural Network to Model Intercellular Gene Regulation from Spatial Transcriptomic Data. Federated Node Classification over Distributed Ego-Networks with Secure Contrastive Embedding Sharing. Enabling Health Data Sharing with Fine-Grained Privacy. MedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1