[1]林欣,温传林,韩立新.一种元搜索主题偏好的排序算法[J].计算机技术与发展,2013,(02):41-43.
 LIN Xin,WEN Chuan-lin,HAN Li-xin.A Ranking Algorithm Based on Topic Preference for Meta-search[J].,2013,(02):41-43.
点击复制

一种元搜索主题偏好的排序算法()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年02期
页码:
41-43
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
A Ranking Algorithm Based on Topic Preference for Meta-search
文章编号:
1673-629X(2013)02-0041-03
作者:
林欣温传林韩立新
河海大学 计算机与信息学院
Author(s):
LIN XinWEN Chuan-linHAN Li-xin
关键词:
元搜索引擎主题偏好排序算法聚类
Keywords:
meta-search enginetopic preferenceranking algorithmclustering
文献标志码:
A
摘要:
元搜索引擎并行地向各个成员搜索引擎发出请求,合并及处理所有成员引擎的返回结果.相对于传统搜索引擎,元搜索引擎具有更好的查全率但在结果相关度排序及查准率方面仍需要改善.就相关度排序及查准率方面的问题元搜索成员引擎对于各个不同主题具有不同的检索质量并就此提出一种基于主题偏好的排序方法.利用Beeferman聚类方法对检索主题划分,通过Borda排序算法对元搜索引擎获得条目进行基于主题的分类排序,以此来提高元搜索查询质量和改善用户体验
Abstract:
Meta-search engine launches query simultaneously to its member search engines and shows a combined and ranked results list. Compared with the traditional search engine,meta-search engine has a better recall rate. However with the large amount of return items from its member engines,the precision rate and MMR still need to be perfected. Each member engine performs differently in the searching tasks with different topics in view of precision rate and MMR. In this paper,present a topic preference based ranking algorithm. Using Beeferman clustering method divides the search topic,with Borda ranking algorithm classify and rank the entries obtained by meta-search engine based on topic,improving the meta-search query quality and enhancing user experience

相似文献/References:

[1]罗江琴 阳小华 马家宇.基于搜索的科研论文自动评价[J].计算机技术与发展,2007,(11):80.
 LUO Jiang-qin,YANG Xiao-hua,MA Jia-yu.Paper Auto- Evaluation Based on Search Engine[J].,2007,(02):80.
[2]严莉莉 王倩倩 孟杰 张燕平.基于聚类的个性化元搜索引擎设计[J].计算机技术与发展,2007,(04):186.
 YAN Li-li,WANG Qian-qian,MENG Jie,et al.Design of Personalized Meta - Search Engine Based on Clustering[J].,2007,(02):186.
[3]沈贺丹 潘亚楠 邵良杉.关于搜索引擎的研究综述[J].计算机技术与发展,2006,(04):147.
 SHEN He-dan,PAN Ya-nan,SHAO Liang-shan.A Study for Search Engine[J].,2006,(02):147.
[4]薛晓慧,芮光辉,李炜东,等.基于排序式 SVM 的搜索自适应排序系统实现[J].计算机技术与发展,2021,31(10):203.[doi:10. 3969 / j. issn. 1673-629X. 2021. 10. 034]
 XUE Xiao-hui,RUI Guang-hui,LI Wei-dong,et al.Implementation of an Adaptive Ranking System for Personalized Search Based on Ranking SVM[J].,2021,31(02):203.[doi:10. 3969 / j. issn. 1673-629X. 2021. 10. 034]

更新日期/Last Update: 1900-01-01