An Approach for Enhancing Aviation Service Satisfaction based on Collaborative Filtering

Abstract

Recently, data analysis technology through artificial intelligence is attracting major attention in various industrial fields. In addition, with the increase in personal income, nowadays, the importance of heterogeneous leisure life is becoming more prominent. However, there is a problem that the tourism industry is not out of the traditional service framework. For the ultimate development of the tourism industry, it is time to provide more scientific and systematic tourism services. In this paper, various data analysis techniques in the field of computer science are applied to the field of tourism to realize next generation tourism services. To this end, the scope of this study is limited to the aviation service, and a natural ecosystem of the aviation industry for future-oriented services of aviation tourism that can improve the efficiency of aviation service gradually is established. The proposed method effectively solves the problems of traditional aviation services through data analysis techniques with artificial intelligence techniques in computer science. We expect that it will enhance the customized satisfaction of customers through personalized service and foster loyal customers in aviation companies through the method proposed.

Fig. 1. International passenger traffic trends from 2012 to 2016 [3].

Fig. 2. Example of the content-based filtering amongCollaborative Filtering Method [4].

Fig. 3. A functional Example of Collaborative Filtering Method.

Fig. 4. An adaptation Result to Aviation Services ofCollaborative Filtering Method.

Table 1. Summary of air transportation performance. [3].

Table 2. The number of international passengers by region (Unit: persons) [3].

Table 3. The change of passenger flight by airline [3].

Table 4. Service items that can be measured in air travel.