Ontology-based trace retrieval

Yonghua Li, J. Cleland-Huang
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引用次数: 30

Abstract

In automated requirements trace retrieval, an ontology can be used as an intermediary artifact to identify relationships that would not be recognized by standard information retrieval techniques. However, ontologies must be carefully constructed to fit the needs of the project. In this paper we present a technique for incorporating information from general and domain-specific ontologies into the tracing process. Our approach applies the domain ontology at the phrase level and then uses a general ontology to augment simple term matching in order to deduce relationships between individual terms weighted according to the relative importance of the phrase in which they occur. The combined weights are used to compute the overall similarity between a source and target artifact in order to establish a candidate trace link. We experimentally evaluated our approach against the standard Vector Space Model (VSM) and show that a domain ontology combined with generalized ontology returned greatest improvements in trace accuracy.
基于本体的跟踪检索
在自动化的需求跟踪检索中,本体可以用作中间工件,以识别标准信息检索技术无法识别的关系。但是,必须仔细构造本体以适应项目的需要。在本文中,我们提出了一种将来自一般本体和特定领域本体的信息合并到跟踪过程中的技术。我们的方法在短语级别应用领域本体,然后使用一般本体来增强简单的术语匹配,以便根据它们出现的短语的相对重要性来推断单个术语之间的关系。组合权重用于计算源和目标工件之间的总体相似性,以便建立候选跟踪链接。我们通过实验对我们的方法与标准向量空间模型(VSM)进行了评估,并表明领域本体与广义本体相结合可以最大程度地提高跟踪精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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