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扩展事件演算以追踪流行病传播。

Extending the event calculus for tracking epidemic spread.

作者信息

Chaudet Hervé

机构信息

Laboratoire d'Informatique Fondamentale, UMR CNRS 6166, Université de la Méditerranée, Faculté de Médecine, 27 bd Jean Moulin, 13385 Marseille Cedex 5, France.

出版信息

Artif Intell Med. 2006 Oct;38(2):137-56. doi: 10.1016/j.artmed.2005.06.001. Epub 2005 Aug 1.

Abstract

OBJECTIVE

The email reporting system has been recognized as a key tool for early warning of disease outbreaks and surveillance of emerging diseases. The aim of the work reported here was to develop a formal language for building an event-centered representation of outbreak histories, described by outbreak reports, which could be used for tracking the spread of epidemics.

METHODS

The SpatioTemporal Extended Event Language (STEEL) we have built is an extension of the Event Calculus that is based on joint spatial and temporal location of event occurrences and structured conglomeration of events. This language allows us to represent and build aggregates of events, according to their spatiotemporal location.

MATERIAL AND RESULTS

In a proof of concept study, this language was implemented in Prolog. A trial corpus of 35 outbreak reports from a PROMED-Mail diffusion list was hand coded in an experimental implementation of STEEL. The performances of this language were compared with three human experts during a question and answer task on this corpus. The experiment showed agreement between responses of the experts and the system.

CONCLUSION

STEEL ensures the spatial and temporal location of event occurrence. The resulting representation is very close to the narrative. Further work must be made to develop a system capable of automatically modeling outbreak reports.

摘要

目的

电子邮件报告系统已被视为疾病暴发早期预警和新发疾病监测的关键工具。本文所报告工作的目的是开发一种形式语言,用于构建以事件为中心的暴发历史表示,由暴发报告描述,可用于追踪疫情的传播。

方法

我们构建的时空扩展事件语言(STEEL)是事件演算的扩展,基于事件发生的联合时空位置和事件的结构化聚集。这种语言使我们能够根据事件的时空位置来表示和构建事件集合。

材料与结果

在一项概念验证研究中,这种语言在Prolog中得以实现。来自PROMED-Mail传播列表的35份暴发报告的试验语料库在STEEL的实验性实现中进行了人工编码。在关于该语料库的问答任务中,将这种语言的性能与三位人类专家进行了比较。实验表明专家的回答与系统之间具有一致性。

结论

STEEL确保了事件发生的时空位置。所得到的表示非常接近叙述内容。必须开展进一步工作来开发一个能够自动对暴发报告进行建模的系统。

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