Ontology alignment process is overwhelmingly cited in Knowledge Engineering as a key mechanism aimed at bypassing heterogeneity and reconciling various data sources, represented by ontologies, i.e., the the Semantic Web cornerstone. In such infrastructures and environments, it is inconceivable to assume that all ontologies covering a particular domain of knowledge are aligned in pairs. Moreover, the high performance of alignment approaches is closely related to two factors, i.e., time consumption and machine resource limitations. Thus, good quality alignments are valuable and it would be appropriate to exploit them. Based on this observation, this article introduces a new method of indirect alignment of ontologies in a cross-lingual context. Indeed, the proposed method deals with alignments of multilingual ontologies and implements an indirect ontology alignment strategy based on a composition and reuse of effective direct alignments. The trigger of the proposed method process is based on alignment algebra which governs the semantics composition of relationships and confidence values. The obtained results, after a thorough and detailed experiment are very encouraging and highlight many positive aspects about the new proposed method.

翻译：在知识工程中,本体调整进程被绝大多数人引用为一种关键机制,目的是绕过异质性,调和各种数据来源,以本体学为代表,即语义网基石。在这种基础设施和环境中,不可想象的是,假设涵盖特定知识领域的所有本体学都是对齐的。此外,本体调整方法的高性能与两个因素密切相关,即时间消耗和机机算资源限制。因此,高质量的调整是有价值的,利用它们是适当的。根据这一观察,本条引入了一种在跨语言背景下间接调整本体学的新方法。事实上,拟议方法涉及多语言本体调整,并在有效直接调整的构成和再利用的基础上实施间接本体调整战略。拟议方法的触发点是调整代数,它制约着关系和信心价值的语义构成。经过彻底和详细的实验后取得的结果非常令人鼓舞,突出了拟议新方法的许多积极方面。