Journey-based information recommendation data processing system

Abstract

The invention relates to a journey-based information recommendation data processing system which comprises a journey information database, a dynamic information database, a processor and a memory in which a computer program is stored. The journey information database is used for storing a user journey record, and the user journey record comprises a user identification field and a journey field; the dynamic information database is used for storing a dynamic information record issued by a user, and the dynamic information record comprises a dynamic information field, a travel tag field and a position tag field. The system can accurately and quickly recommend the information to each user directionally based on the journey information.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a data processing system for information recommendation based on itinerary. Background technique [0002] In order to provide users with richer travel information, solve the problems of user freshness and boredom, and improve the experience, the flight tool app has added a travel information recommendation function. In the existing travel information recommendation technologies, the recommendation methods are not closely related to the itinerary information, and do not combine the user's itinerary information to recommend more relevant information. [0003] In some travel information recommendation systems, users can only comment and like the officially released information, but cannot publish content. The degree of information interaction is low, and the recommended content is only divided into two categories: the latest and the hottest. All the content that users see T...

AI Technical Summary

Problems solved by technology

[0003] In some travel information recommendation systems, users can only comment and like the official news information, but cannot publish content. The degree of information interaction is low, and the recommended content is only divided into two categories: latest and popular. All the content that users see They are all the same, without personalization, and the accuracy of information recommendation is low

In other aviation and travel information recommendation systems, although users are supported to publish content, the target users are civil aviation staff, and the published content must be reviewed, the process is relatively cumbersome, and the efficiency of information recommendation is low

Although some existing travel information recommendation systems can associate flight and airport tags when publishing content, they do not use these tags when recommending, but only show the relevant flights and airports

Moreover, only authenticated staff accounts can click on the airport label to see other content of the same airport. Ordinary passenger users can only see the content recommended by the home page list, which is not friendly

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