Historians, and in particular researchers in prosopography, focus a lot of effort on extracting and coding information from historical sources to build databases. To deal with this situation, they rely in some cases on their intuition. One important issue is to provide these researchers with the information extracted from the sources in a sufficiently structured form to allow the databases to be queried and to verify, and possibly, to validate hypotheses. The research in this paper attempts to take up the challenge of helping historians capturing and assessing information throughout automatic processes. The issue emerges when too many sources of uncertain information are available. Based on the high-level information fusion approach, we propose a process that automatically supports historians' intuition in the domain of prosopography. The contribution is threefold: a conceptual data model, a process model, and a set of rules combining the reliability of sources and the credibility of information.
翻译:历史学家,特别是人造图学研究人员,将大量精力集中于从历史来源提取和编码信息,以建立数据库。为了应对这种情况,他们有时依靠直觉。一个重要问题是,向这些研究人员提供从来源提取的信息,其结构应足够完善,以便查询数据库,核实并可能的话验证假想。本文件的研究试图迎接帮助历史学家在整个自动过程中收集和评估信息的挑战。当有太多不确定信息来源时,问题就出现了。根据高层次信息聚合方法,我们提议了一个自动支持历史学家在编程学领域的直觉的过程。贡献有三重:概念数据模型、过程模型以及一套将资料来源的可靠性和信息可信度相结合的规则。