通过时间序列分析检测季节性查询

Milad Shokouhi
{"title":"通过时间序列分析检测季节性查询","authors":"Milad Shokouhi","doi":"10.1145/2009916.2010104","DOIUrl":null,"url":null,"abstract":"Seasonal events such as Halloween and Christmas repeat every year and initiate several temporal information needs. The impact of such events on users is often reflected in search logs in form of seasonal spikes in the frequency of related queries (e.g. \"halloween costumes\", \"where is santa\"). Many seasonal queries such as \"sigir conference\" mainly target fresh pages (e.g. sigir2011.org) that have less usage data such as clicks and anchor-text compared to older alternatives (e.g.sigir2009.org). Thus, it is important for search engines to correctly identify seasonal queries and make sure that their results are temporally reordered if necessary. In this poster, we focus on detecting seasonal queries using time-series analysis. We demonstrate that the seasonality of a query can be determined with high accuracy according to its historical frequency distribution.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"81","resultStr":"{\"title\":\"Detecting seasonal queries by time-series analysis\",\"authors\":\"Milad Shokouhi\",\"doi\":\"10.1145/2009916.2010104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Seasonal events such as Halloween and Christmas repeat every year and initiate several temporal information needs. The impact of such events on users is often reflected in search logs in form of seasonal spikes in the frequency of related queries (e.g. \\\"halloween costumes\\\", \\\"where is santa\\\"). Many seasonal queries such as \\\"sigir conference\\\" mainly target fresh pages (e.g. sigir2011.org) that have less usage data such as clicks and anchor-text compared to older alternatives (e.g.sigir2009.org). Thus, it is important for search engines to correctly identify seasonal queries and make sure that their results are temporally reordered if necessary. In this poster, we focus on detecting seasonal queries using time-series analysis. We demonstrate that the seasonality of a query can be determined with high accuracy according to its historical frequency distribution.\",\"PeriodicalId\":356580,\"journal\":{\"name\":\"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"81\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2009916.2010104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2009916.2010104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 81

摘要

像万圣节和圣诞节这样的季节性事件每年都会重复,并引发一些时间信息需求。这些事件对用户的影响通常以相关查询频率的季节性峰值形式反映在搜索日志中(例如:“万圣节服装”,“圣诞老人在哪里”)。许多季节性查询,如“sigir conference”,主要针对的是新页面(如sigir2011.org),与旧的替代品(如sigir2009.org)相比,这些页面有更少的使用数据,如点击和锚文本。因此,对于搜索引擎来说,正确识别季节性查询并确保其结果在必要时临时重新排序是很重要的。在这张海报中,我们专注于使用时间序列分析来检测季节性查询。我们证明了根据查询的历史频率分布可以高精度地确定查询的季节性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting seasonal queries by time-series analysis
Seasonal events such as Halloween and Christmas repeat every year and initiate several temporal information needs. The impact of such events on users is often reflected in search logs in form of seasonal spikes in the frequency of related queries (e.g. "halloween costumes", "where is santa"). Many seasonal queries such as "sigir conference" mainly target fresh pages (e.g. sigir2011.org) that have less usage data such as clicks and anchor-text compared to older alternatives (e.g.sigir2009.org). Thus, it is important for search engines to correctly identify seasonal queries and make sure that their results are temporally reordered if necessary. In this poster, we focus on detecting seasonal queries using time-series analysis. We demonstrate that the seasonality of a query can be determined with high accuracy according to its historical frequency distribution.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信