Query expansion methods for collaborative information retrieval

被引:4
作者
Hust, Armin [1 ]
机构
[1] Univ Kaiserslautern, Comp Sci Econ & Math, Kaiserslautern, Germany
来源
COMPUTER SCIENCE-RESEARCH AND DEVELOPMENT | 2005年 / 19卷 / 04期
基金
英国科研创新办公室;
关键词
Information retrieval; Text mining; Query expansion; Collaborative information retrieval;
D O I
10.1007/s00450-004-0174-4
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
The accuracy of ad-hoc document retrieval systems has reached a stable plateau in the last few years. We are working on so-called collaborative information retrieval (CIR) systems which have the potential to overcome the current limits. We define CIR as a task, where an information retrieval (IR) system uses information gathered from previous search processes from one or several users to improve retrieval performance for the current user searching for information. We focus on a restricted setting in CIR in which only old queries and correct answer documents to these queries are available for improving a new query. For this restricted setting we propose new approaches for query expansion procedures. We show how CIR methods can improve overall IR performance.
引用
收藏
页码:224 / 238
页数:15
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