动态需求跟踪中多义关键词的语义判断方法

虽然与信息检索(IR)方法相比,基于本体的动态需求跟踪方法能提高跟踪链的精度,但构建一个合理、有效的本体特别是领域本体是一个相当复杂和繁琐的过程。为了减小构建领域本体带来的时间成本和人力成本,通过将修饰词和通用本体相结合,提出基于修饰词本体的关键词语义判断方法(MOKSJM)。首先,对关键词和修饰词的搭配关系进行分析;然后,采用修饰词本体结合规则的方式来确定关键词的语义,以避免关键词的多义性对动态需求跟踪结果造成的偏差;最后,根据上述分析的结果,对关键词语义作出调整,并通过相似度得分来体现其语义。修饰词在需求文档、设计文档等中数量较少,因此建立修饰词本体所带来的时间成本和人力成本相对较小。实验结果表明,MOKSJM与基于领域本体的动态跟踪方法在召回率相当时,精度差距更小;与向量空间模型(VSM)方法相比,MOKSJM能有效提高需求跟踪结果的精度。

Semantic judgement method of polysemous keywords in dynamic requirement traceability

Although ontology-based dynamic requirement traceability methods can improve the accuracy of trace links compared with Information Retrieval (IR), but it is rather complicated and tedious to construct a reasonable and effective ontology, especially domain ontology. In order to reduce time cost and labor cost brought by the domain ontology construction, a Modifier Ontology-based Keyword Semantic Judgment Method (MOKSJM) which combined modifiers with general ontology was proposed. Firstly, the collocation relationship between keywords and modifiers was analyzed. Then, the semantics of keywords were determined by combining modifier ontologies with rules, so as to avoid the bias of dynamic requirements traceability results caused by the polysemy of keywords. Finally, based on results of the above analysis, the semantics of keywords were adjusted and reflected by similarity scores. The number of modifiers is small in the requirements document, design documents, etc., so the time cost and labor cost brought by establishing the modifier ontology is relatively small. The experimental results show that compared to domain ontology-based dynamic requirement traceability method, MOKSJM has a small gap in precision with the same recall rate, and when compared to Vector Space Model (VSM) method, MOKSJM can effectively improve the accuracy of the requirements traceability result.