A simple kernel co-occurrence-based enhancement for pseudo-relevance feedback

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：

Pan, Min;Huang, Jimmy Xiangji*;He, Tingting（何婷婷）;Mao, Zhiming;Ying, Zhiwei;...

通讯作者：

Huang, Jimmy Xiangji

作者机构：

[Pan, Min] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Informat Retrieval & Knowledge Management Res Lab, Wuhan, Peoples R China.

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

[Huang, Jimmy Xiangji; Pan, Min; Ying, Zhiwei] York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON, Canada.

[He, Tingting; Tu, Xinhui; Mao, Zhiming] Cent China Normal Univ, Sch Comp, Informat Retrieval & Knowledge Management Res Lab, Wuhan, Peoples R China.

[Ying, Zhiwei] Cent China Normal Univ, Sch Informat Management, Informat Retrieval & Knowledge Management Res Lab, Wuhan, Peoples R China.

通讯机构：

[Huang, Jimmy Xiangji] Y

York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON, Canada.

语种：

英文

关键词：

Co-occurrence informations;Co-occurrence relationships;Pseudo relevance feedback;Query expansion techniques;Retrieval performance;State-of-the-art approach;Text retrieval conferences;Traditional models;Information retrieval;article;human;human experiment;information retrieval;language

期刊：

JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY

ISSN：

2330-1635

年：

2020

卷：

期：

页码：

264-281

DOI：

10.1002/asi.24241

基金类别：

This research was substantially supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada, an NSERC CREATE award in ADERSIM, the York Research Chairs (YRC) program, and an Ontario Research Fund-Research Excellence (ORF-RE) award in BRAIN Alliance. This research is also supported by the National Natural Science Foundation of China (61572223, 61532008). We thank the Ph.D. students FangHong Jian and Hao Hu for their help with the experiments. We greatly appreciate three anonymous reviewers and the associate editor for their valuable and excellent review comments that greatly helped to improve the quality of this article.

机构署名：

本校为第一机构

院系归属：

计算机学院

信息管理学院

国家数字化学习工程技术研究中心

摘要：

Pseudo-relevance feedback is a well-studied query expansion technique in which it is assumed that the top-ranked documents in an initial set of retrieval results are relevant and expansion terms are then extracted from those documents. When selecting expansion terms, most traditional models do not simultaneously consider term frequency and the co-occurrence relationships between candidate terms and query terms. Intuitively, however, a term that has a higher co-occurrence with a query term is more likely to be related to the query topic. In this article, we propose a kernel co-occurrence-based ...

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 simple kernel co-occurrence-based enhancement for pseudo-relevance feedback

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