查询会话中带时间因子的隐式负反馈研究  

Exploration of Implicit Negative Feedback with Time Factorin Search Session

作　　者：陈振宏[1,2] 俞晓明[1] 刘悦[1] 程学旗[1] 

机构地区：[1]中国科学院计算技术研究所,北京100190 [2]中国科学院大学,北京100190

出　　处：《中文信息学报》2016年第2期113-120,共8页Journal of Chinese Information Processing

基　　金：国家重点基础研究发展计划(973)(2012CB316303;2014CB340401);国家高技术研究发展计划(863)(2014AA015204;2014AA015103);国家自然科学基金(61232010);国家杰出青年科学基金(61425016);中国科学院重点部署项目(KGZD-EW-T03-2)

摘　　要：隐式相关反馈常被用于提升检索系统的性能,目前大部分工作集中在研究隐式正反馈。该文同时考虑隐式正负反馈,将查询会话中被点击网页前的未被点击网页作为隐式负反馈信息,通过引入时间因子,估计用户在未被点击网页的标题和摘要上的停留时间,推断隐式负反馈与用户兴趣和行为的关系,达到优化检索结果的目的。在TREC Session 2011和2012数据集上的实验,验证了该文提出的带时间因子的隐式正负反馈算法TIPNF的有效性。Implicit relevance feedback has been used to improve the performance of the retrieve system.In Contrast to the recent,most of the related work focusing on implicit positive feedback,this paperinvestigated the usefulness of combining both implicit positive and negative feedback with time factor.The implicit negative feedback used in this paper is the unclicked document before the clicked document in the same search session.By estimating the time spent on the title and snippet of the unclicked document,the time factor is introduced to infer the relationships between user＇s interest and behaviors.Thus,a unified time factor model called TIPNF is proposed to use both implicit positive and negative feedback to improve the performance of the retrieve system.Experiments on TREC Session2011 and 2012verify the effectiveness and stabilization of the TIPNF.

关 键 词：查询会话 隐式负反馈 时间因子 排序 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]