Deja-Vu -- A mechanism for constructing dialogue memory for resource-bounded agents

在与计算机系统交互期间提供上下文信息的能力具有改善用户整体体验的巨大潜力。我们建议以自动生成的、不断更新的“对话记忆”的形式发展这种能力，该记忆可驻留在服务器站点或个人用户的个人数字助理中。这种记忆将通过一种新的方法产生，该方法结合了自然语言技术来提取对话特征，模型选择技术来对相关对话进行聚类，以及认知建模技术来剪除所产生的记忆。所实施的计算机系统将在故障排除对话领域进行测试。

The ability to provide contextual information during interactions with computer systems has great potential to improve the overall experience for users. We propose to develop such an ability in the form of an automatically generated, continuously updated ``dialogue memory'', which may reside at server sites or in the PDAs of individual users. This memory will be generated by means of a novel approach which combines Natural Language techniques to extract dialogue features, model-selection techniques to cluster related dialogues, and cognitive modeling techniques to prune the resultant memories. The implemented computer system will be tested in the domain of trouble-shooting dialogues.