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From NL Preference Expressions to Comparative Preference Statements: A Preliminary Study in Eliciting Preferences for Customised Decision Support

机译:从NL偏好表达到比较偏好陈述:为定制化决策支持选择偏好的初步研究

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Intelligent 'services' are increasingly used on e-commerce platforms to provide assistance to customers. Numerous preference elicitation methods developed in the literature are now employed for this purpose. However, it is commonly known that there is a real bottleneck in preference handling as concerns the elicitation of preferences because it does not cater to the wide range of preference representation languages available. Thus, as a first step in developing a decision-support tool using an AI based on such languages, this paper describes a preliminary study conducted to address this issue. We propose a method of eliciting real-time user preferences expressed in natural language (NL) which can be formally represented using comparative preference statements complying with different semantics, and provide a proof of concept to demonstrate its feasibility. Since we develop NL resources to detect preference semantics, we also make a comparative study with existing resources to underline the peculiarities of our model.
机译:智能“服务”越来越多地用于电子商务平台上,以向客户提供帮助。为此目的,现在采用了文献中开发的许多偏好激发方法。然而,众所周知,关于偏好的引发,偏好处理中存在真正的瓶颈,因为它不能满足广泛的可用偏好表示语言的要求。因此,作为使用基于此类语言的AI开发决策支持工具的第一步,本文描述了为解决此问题而进行的初步研究。我们提出了一种以自然语言(NL)表示的实时用户偏好的方法,该方法可以使用符合不同语义的比较偏好语句来正式表示,并提供概念证明以证明其可行性。由于我们开发了NL资源来检测偏好语义,因此我们也与现有资源进行了比较研究,以强调模型的特殊性。

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