A Pseudo-relevance feedback framework combining relevance matching and semantic matching for information retrieval

首页 > 成果 > 详情

认领

导出

Link by DOI

反馈

作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Wang, Junmei;Pan, Min;He, Tingting*（何婷婷）;Huang, Xiang;Wang, Xueyan;...

通讯作者：

He, Tingting

作者机构：

[Wang, Junmei] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.

[Pan, Min] Hubei Normal Univ, Sch Comp & Informat Engn, Huangshi 435002, Hubei, Peoples R China.

[He, Tingting; Wang, Xueyan; Tu, Xinhui; Huang, Xiang] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.

[He, Tingting; Wang, Junmei; Wang, Xueyan; Tu, Xinhui; Pan, Min; Huang, Xiang] Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan 430079, Peoples R China.

[He, Tingting; Wang, Junmei; Wang, Xueyan; Tu, Xinhui; Pan, Min; Huang, Xiang] Natl Language Resources Monitor & Res Ctr Network, Wuhan 430079, Peoples R China.

通讯机构：

[He, Tingting] C

[He, Tingting] H

[He, Tingting] N

Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.

Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan 430079, Peoples R China.

语种：

英文

关键词：

Information retrieval;Pseudo-relevance feedback;Semantic matching;Text similarity

期刊：

Information Processing & Management

ISSN：

0306-4573

年：

2020

卷：

期：

页码：

102342

DOI：

10.1016/j.ipm.2020.102342

基金类别：

This research is supported by the National Natural Science Foundation of China (61532008), the National Natural Science Foundation of China (61572223), the National Key Research and Development Program of China (2017YFC0909502), and Wuhan Science and Technology Program (2019010701011392). This work was partly supported by the innovation team of the basic intelligent education service innovation model and technology research, in Hubei Normal University.

机构署名：

本校为第一且通讯机构

院系归属：

数学与统计学学院

计算机学院

摘要：

Pseudo-relevance feedback (PRF) is a well-known method for addressing the mismatch between query intention and query representation. Most current PRF methods consider relevance matching only from the perspective of terms used to sort feedback documents, thus possibly leading to a semantic gap between query representation and document representation. In this work, a PRF framework that combines relevance matching and semantic matching is proposed to improve the quality of feedback documents. Specifically, in the first round of retrieval, we propose a reranking mechanism in which the information ...

反馈

产权有误：本人成果被他人认领

数据有误：数据基本信息有误

归属有误：成果的院系归属、机构署名归属有误

其他原因：

验证码：

看不清楚，换一个

确定

取消

成果认领

标题：

用户	作者	通讯作者	--
	请选择	请选择	--

确定

取消

A Pseudo-relevance feedback framework combining relevance matching and semantic matching for information retrieval

反馈

成果认领

提示

该栏目需要登录且有访问权限才可以访问