面向内容和结构的XML检索相关反馈方法

L. Hlaoua, M. Boughanem, K. Pinel-Sauvagnat
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引用次数: 1

摘要

传统的信息检索(Information Retrieval, IR)将整个文档视为检索的原子单元,而XML IR将XML元素作为可能的检索单元来处理。在考虑XML文档中的相关性反馈(RF)时,出现了许多悬而未决的问题。它们主要与混合了内容和结构的XML文档的形式以及信息检索系统(information Retrieval Systems, IRS)处理的信息的新粒度有关。XML检索中提出的大多数RF方法都是对传统RF的简单改编,以适应新的信息粒度。它们通过添加从相关元素中提取的术语而不是从整个文档中提取的术语来丰富查询。在本文中,我们建议通过添加内容约束和结构约束来扩展初始查询。在INEX评估活动中进行了实验,结果表明了我们的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using a Content-and-Structure Oriented Method for Relevance Feedback in XML Retrieval
As opposed to traditional Information Retrieval (IR) which views whole documents as atomic units of retrieval, XML IR processes XML elements as possible units of retrieval. Many open issues appear when considering Relevance Feedback (RF) in XML documents. They are mainly related to the form of XML documents that mix content and structure and to the new granularity of information processed by the Information Retrieval Systems (IRS). Most of the RF approaches proposed in XML retrieval are simple adaptations of traditional RF to the new granularity of information. They enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. In this paper, we propose to extend the initial query by adding both content and structural constraints. Experiments are carried out with the INEX evaluation campaign and results show the interest of our method.
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