System for establishing self-service based on passenger market behavior characteristics

Abstract

The invention provides a system for establishing the self-service based on the passenger market behavior characteristics, which belongs to the technical field of aviation and comprises a neighborhoodrecommendation system, a time sequence recommendation system and/or a passenger label system. An implementation mode of the neighborhood recommendation system comprises the steps of establishing a passenger-commodity interest degree matrix; screening a passenger set similar to the interest of the target user; utilizing the interest similarity among the passengers to find the commodity that the passengers prefer, and the target user does not inquire or purchase to recommend to the target user, so that the problem of recommending the commodities that the passengers do not know but may be interested to the passengers, is solved.

Description

technical field [0001] The invention belongs to the field of aviation technology, and in particular relates to a system for establishing self-service based on passenger market behavior characteristics. Background technique [0002] In traditional airport research, in order to conduct research on the market characteristics of airport passengers, it is first necessary to conduct a preliminary segmentation of the passenger market according to market theory, and then formulate passenger research needs according to the development goals of the airport, so as to formulate research plans and implement passenger research, and finally Analyze and verify the research results, obtain valuable segmentation and market feedback, and form the passenger market segmentation, market positioning and market demand of the coach project. At present, there is a lack of self-service systems based on passenger market behavior characteristics in the market. Contents of the invention [0003] The p...

AI Technical Summary

Problems solved by technology

[0005] Compared with the prior art, the advantages and positive effects of the present invention are: the present invention studies the characteristics of airport passengers under big data, and focuses on how to recommend products that passengers do not know but may be interested in.