Understanding Complex Behavior and Decision Making Using Ethnographic Knowledge Elicitation Tools (KnETs)
Understanding Complex Behavior and Decision Making Using Ethnographic Knowledge Elicitation Tools (KnETs)
复制标题
使用民族志知识获取工具 (KnET) 了解复杂的行为和决策
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
S. Bharwani
中科院分区：
文献类型：
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作者：
S. Bharwani
当面对人类在其环境中的多种反应时，以正式的方式理解民族志数据是必要的。知识获取工具（Knowledge）结合了使用人类学田野调查中长期使用的方法建模知识的技术，以及使用计算机科学中的知识工程方法将知识形式化的技术。Knowledge增强了我们对数据的理解，揭示了新的查询途径。Knowledge支持传统的参与式实地工作方法，并为基于代理的模型提供投入，支持知识的定性和定量表示及其相互作用之间的正式联系。这些技术的融合产生了一个四阶段的过程，其中包括对领域专家和线人收集的数据进行一致的验证和确认。这种创新方法的应用是成功的，正是由于每种技术提供了解决目前的瓶颈，在民族志数据收集和知识工程的过程中的互利。
Understanding ethnographic data in a formal way is imperative when faced with multiple responses of humans within their environments. Knowledge Elicitation Tools (KnETs) incorporate techniques for modeling knowledge using methods long used in anthropological fieldwork and formalizing knowledge using knowledge engineering methods from computer science. KnETs enhance our understanding of our data to reveal new avenues for enquiry. KnETs support traditional participatory fieldwork methods and produce input for agent-based models, supporting a formalized link between qualitative and quantitative representations of knowledge and their interaction. The fusion of these techniques has resulted in a four-stage process that incorporates consistent verification and validation on data as it is collected by domain experts and informants. The application of this innovative methodology is successful precisely due to the mutual benefits that each technique provides by addressing current bottlenecks in both processes of ethnographic data collection and knowledge engineering.