Domain-Aware Data Matching in Emergency Response Scenarios

如今，来自不同领域的参与者需要进行协作的情况很多。例如，在紧急响应(ER)情况下，不同机构必须共同努力，以尽快恢复正常。然而，这种合作并不容易，因为参与这类情景的机构以不同的方式介绍知识。虽然有一些技术被应用来解决这种异构性问题，但这些技术有时会由于机构之间的歧义和不同的知识表示程度(专业化)而导致不匹配。在这项研究中，我们将使用领域特定的术语来解决这些问题，实例化我们对ER场景的方法。在这一点上，我们正在形式化ER机构的术语。具体地说，我们采用了英国民事和保护术语表中的术语，该术语表包含了英国ER组织使用的常用术语。下一步是将这些特定术语集成到词汇资源(WordNet)中，并使用这些新术语在不同机构的模式之间进行语义匹配。因此，我们将利用领域信息来解决歧义和专门化问题。

Nowadays, there are a lot of situations where participants from different domains have to collaborate. For example, in emergency response (ER) scenarios different agencies have to work together in order to reestablish normality as fast as possible. Nevertheless, this cooperation is not easy because the agencies involved in such scenarios represent knowledge in different ways. Although there are applied some techniques in order to address this heterogeneity problem, these sometimes produce mismatches caused by ambiguity and different knowledge representation degree between agencies (specialisation). In this research we are going to use domain-specific terminologies, to tackle these problems, instantiating our approaches into ER scenarios.At this point, we are formalising terminologies from ER agencies. Concretly, we are taking terms from the UK Civil and Protection glossary, which cotains common terms used by ER organisations in the UK. The next step consist in integrating these specific terms into a lexical resource (WordNet) and using these new terms to carry out semantic matchings between different agencies' schemas. Thus, we are going to take advantage of domain information in order to takle ambiguity and specialisation.