Effects of Terms Recognition Mistakes on Requests Processing for Interactive Information Retrieval

Author:

Omri Mohamed Nazih1

Affiliation:

1. MARS Research Unit, Department of Computer Sciences, Faculty of Sciences of Monastir, University of Monastir, Monastir, Tunisia

Abstract

In this work the author proposes to describe a new model of information retrieval. They studied the effects of using weighted index terms recognition mistakes in a document indexing system and evaluate indexing performance when short and long requests are used. The effect of weighting index terms in the document collection and in the requests is analyzed. Given the typical requests submitted to term indexing system, it seems easy to consider that the effects of term recognition mistakes in user requests must be severely destructive on the effectiveness of the system. The experimental study reported in this paper shows that the use of classical term Indexing technique for processing this kind of request is robust to considerably high levels of term recognition mistakes, in particular for long requests. Moreover, both standard pertinence feedback and pseudo pertinence feedback can be employed to improve the effectiveness of user request processing.

Publisher

IGI Global

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fuzzy Ontology-Based Querying User' Requests Under Uncertain Environment;International Journal of Cognitive Informatics and Natural Intelligence;2020-07

2. Uncertain Confidence Network-Based Collaborative Information Retrieval Relevance Feedback Algorithm;Advances in Library and Information Science;2020

3. Information Retrieval Model Using Uncertain Confidence's Network;Information Retrieval and Management;2018

4. Collaborative Information Retrieval Model Based on Fuzzy Clustering;2017 International Conference on High Performance Computing & Simulation (HPCS);2017-07

5. Information Retrieval Model using Uncertain Confidence's Network;International Journal of Information Retrieval Research;2017-04

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3