支持搜索结果多样化的排名算法比较研究

doi:10.3969/j.issn.1000-3428.2016.10.008

摘要/Abstract

摘要： 近年来在信息检索领域研究人员提出了多种支持结果多样化的排名算法,但还没有相关文献对这些算法的性能进行系统的分析和比较。为此,在数据融合排名算法CombSum的基础上,提出一种同时考虑文档相关性和多样性的排名算法CombSumDiv,并将其与xQuAD和PM2这2种显式排名算法进行性能比较。在TREC多样性任务提供的查询数据集和ClueWeb09B数据集上的实验结果表明,CombSumDiv查询性能较优、xQuAD次之、PM2较差,且3种算法均具有较强的稳定性及抗干扰能力。

关键词: 数据融合, 搜索结果多样化, 重排, 稳定性, 检索评价

Abstract: Recently,researchers in the field of information retrieval have proposed many ranking algorithms supporting search result diversification,but there is no literature on the performance analysis and comparison of these algorithms.Based on a traditional data fusion ranking algorithm CombSum,this paper proposes a new ranking algorithm CombSumDiv,which considers relevance and diversity of the documents at the same time.Besides,a comparison among CombSumDiv and two explicit ranking algorithms xQuAD and PM2 is conducted.Experiments are carried out with query datasets and ClueWeb09B datasets from the TREC diversity task.The result shows that the query performance of CombSumDiv algorithm is better than that of xQuAD and PM2 algorithm,and these three algorithms have strong stability and anti-interference ability.

Key words: data fusion, search result diversification, re-ranking, stability, retrieval evaluation

中图分类号:

TP391.3

陈婷婷,黄春兰,吴胜利. 支持搜索结果多样化的排名算法比较研究[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2016.10.008.

CHEN Tingting,HUANG Chunlan,WU Shengli. Comparative Study of Ranking Algorithms Supporting Search Result Diversification[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2016.10.008.

https://www.ecice06.com/CN/Y2016/V42/I10/45

参考文献

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