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

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.