就我个人而言:用对话助手来开发和评估一种含义维度的本体学,用于自我揭示
Libby Ferland1, Hannah Qu2, Wilma Koutstaal2
1Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.
PloS one
|February 20, 2026
概括
我们提出了一种新的本体学,用于理解对话系统中的用户自我披露. 这一框架有助于对话式AI更好地解释用户信息,以改善参与和建立关系.
科学领域:
- 人与计算机的交互
- 人工智能的人工智能
- 计算语言学 计算语言学
背景情况:
- 对话系统和对话助手在长期用户采用方面面临挑战.
- 用户参与与用户和人工智能代理之间的关系形成有关.
- 自我揭露对于建立人类关系至关重要,并且发生在人与人工智能的互动中.
研究的目的:
- 解决了解对话系统中自我披露的多面性质的差距.
- 提出一种新的本体论,用于在人与人工智能交互中自我披露.
- 增强对话性AI解释和利用用户自我披露的能力.
主要方法:
- 为对话系统开发了一个全面的自我披露本体学.
- 包括主题,亲密和心理动词 (例如习惯,偏好,记忆) 等维度.
- 应用了本体学来分析来自真实用户对话系统交互的自我披露实例.
主要成果:
- 展示了拟议的本体学的应用到现实世界的对话数据.
- 检查了自我披露意义的不同维度之间的相互关系.
- 突出了本体学的潜力,为AI代理人提取有价值的信息.
结论:
- 对话系统中的自我披露是一个复杂的,相互关联的现象.
- 拟议的本体论提供了一个结构化的方法来分析用户的自我披露.
- 这一框架为设计更具吸引力和有效的对话性AI提供了实际意义.
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