Tourism information recommending method and device

Abstract

The invention discloses a tourism information recommending method and device. The method includes a user information obtaining step: acquiring the data of a first user, wherein the first user data comprises identity information of the first user and the history information of the user; a recommendation information generating step: inputting the data of the first user into a trained deep neural network, generating a travel information recommendation result which represents a probability that the first user will go to at least one tourist attraction, wherein the deep neural network is obtained through a training step, and the training step comprises a user data making step, an tourist attraction data acquisition step, a model prediction step, and a model correction step. The method adopts amachine learning method to automatically recommend the tourist attractions for the user by acquiring and analyzing the user's behavior data, which saves the user's time and brings a brand new and better user experience.

Description

technical field [0001] The present application relates to the field of information processing, in particular to a method and device for recommending travel information. Background technique [0002] At present, when an application program (APP) about tourism recommends tourist attractions for users, the following methods are generally adopted. One method is to require the user to choose the target scenic spot they want to go to, recommend the scenic spot according to the user's choice, and make an itinerary. This method requires the user to input the target scenic spot and calculate it. , this method is not applicable, so it is less practical and not suitable for the general public. There is another method that is done manually by a professional customizer of a travel agency. First, the customizer needs to know a lot of travel information and information, and has a good understanding of the characteristics of each place; secondly, the customizer needs to spend a lot of time...

AI Technical Summary

Problems solved by technology

One method is to require the user to choose the target scenic spot they want to go to, recommend the scenic spot according to the user's choice, and make an itinerary. This method requires the user to input the target scenic spot and calculate it. , this method is not applicable, so the practicality is low, and it is not suitable for the general public

There is another method that is done manually by a professional customizer of a travel agency. First, the customizer needs to know a lot of travel information and information, and has a good understanding of the characteristics of each place; secondly, the customizer needs to spend a lot of time communicating with users and according to the communication As a result, adjusting the recommended scenic spots requires a lot of human resources and is very inefficient

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