Real time key element extraction for design of in flight meal services based on passenger's personality traits

Abstract

In flight meal services is one of the most important points to judge an airline as favorite to the passengers. It is crucial to include personal trait in designing these services. Thus, this work concentrated on formulating model of in-flight meal services. First, by using Key Element Extraction (KEE), we identify passenger's personality traits in real time from social media. And then we design model formulation of in-flight meal services, by using Quantification Theory Type 1 (QTT1). The identification of passenger's personality traits in computational experiment are based on particular type such as neophobia, variety seeking selective, and variety seeking. Variants formulation for each personality traits were designed for different categories such as menu variant, originality, appearance, suitability, cordiality, punctually and responsibility. To enabling implementation of this model, it is required to attach it to the current booking and database costumer system that running online.