A Personalized Tourist Information Screening Method Matching User Characteristics

Abstract

The invention provides an individualized travel information screening method matching user characteristics. The individualized travel information screening method comprises individualized demand modeling and mapping rule modeling. The individualized requirement modeling comprises entity demand modeling and line demand modeling, wherein the entity demand modeling adopts a two-layer granularity classification method to carry out classification processing on entity demand parameters and the line demand modeling adopts a three-layer granularity classification method to carry out classification processing on all line demands. The mapping rule modeling comprises a mapping algorithm and a recommended algorithm. According to the individualized travel information screening method provided by the invention, an individualized algorithm matching the user characteristics is designed to aim at the characteristics that the total user quantity of travel industries is great, the total historical data quantity is abundant, the single user data quantity is small and the like: after a user logs in a system, no parameters are needed to be input; and travel services which are the most needed can be initiatively recommended to the user according to the user characteristics, so that the individualized demands of the user are satisfied and a lot of time of the user is shortened.

Description

technical field [0001] The invention belongs to the field of travel information services, and in particular relates to a screening method for personalized travel information matching user characteristics. Background technique [0002] At present, most tourism enterprises provide various information services through which tourists can obtain relevant tourism information such as attractions, travel routes and quotations. However, these services are set up by enterprises, mostly from the perspective of enterprises, ignoring the main status of users, and the recommended information services are stereotyped, which often cannot reflect the individual needs of users. [0003] At present, the personalized algorithms used for tourism information screening are closely related to the application scenarios. The personalized algorithms mainly include the following categories: [0004] (1) Content-based recommendation algorithm [0005] The theoretical basis of the content-based informa...

AI Technical Summary

Problems solved by technology

The disadvantages of this algorithm are: it requires rich historical data of users; it cannot make accurate recommendations for newly added items

The main disadvantage of this algorithm is: the establishment of rules and logical rationality is a rather complicated process

Therefore, the traditional method of obtaining individual needs of individual users based on logical rules from individual user historical data cannot be adapted to tourism services, especially for those new users.

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