Personalized travel package recommendation method based on demand classification and subject analysis

Abstract

The invention relates to a personalized travel package recommendation method based on demand classification and subject analysis. The method includes: analyzing natural language form demands input by a user, utilizing word segmentation, demand classification and other natural language processing techniques to process and classify the user demands so as to obtain rigid demand, flexible demand and negative demand of the user; then utilizing an LDA (latent dirichlet allocation) document theme generation model, making travel service individuals effectively cluster into different service fields by theme similarity, and then conducting similarity matching with the user demands so as to obtain a service list best matching user expectation; finally carrying out travel package design recommendation by means of travel package optimized recommendation algorithm: firstly acquiring a travel package scenic spot set according to user time demand and service priority information; then combining location information, preference information and the like to determine travel package hotel service; and then calculating the optimal journey of every day according to the distance function L, and ranking the travel package according to travel package recommendation index; and finally, selecting travel package catering service according to scenic spot location and user preference. By integrating the processing, the purpose of designing and recommending personalized travel package best meeting the user demand can be realized.

Description

technical field [0001] The invention relates to a personalized travel bag recommendation method based on demand classification and subject analysis. This method extracts the requirements from the user's input and classifies the content of the requirements; combined with topic analysis, it generates a set of alternative services; on this basis, it uses the travel bag optimization recommendation method to design and recommend travel bags for users. The method belongs to the field of computer system modeling and data analysis. Background technique [0002] In recent years, with the rapid development of Internet technology and the continuous improvement of people's living standards, the online travel industry has developed rapidly, and with the rise of Service Oriented Computing (SOC for short), people are used to viewing it with the concept of service Each individual tourism product (such as attractions, hotels, etc.), and look at travel package recommendation from the perspec...

AI Technical Summary

Problems solved by technology

Although users can search and find interesting travel services on traditional online travel platforms, due to the large amount of Internet information and a large amount of useless information, users' search efficiency is reduced, and it is difficult to quickly find services that meet their needs;

[0004] 2) Lack of personalized customization services

However, these solutions are all fixed (either fixed products provided by travel agencies, or fixed strategies released by "donkey friends"), and the needs of users are often changeable, and it is difficult to find a forming solution that fully meets the requirements. This requires online travel platforms to automatically and autonomously generate new personalized solutions, that is, travel bags, according to user needs, and recommend them to users;

[0005] 3) Cannot handle users' natural language needs

At present, most online travel platforms require users to choose information such as travel destinations, tour days, and travel budgets in the form of fixed options, but the fixed options provided by the platforms generally cannot cover all possible needs of users

For users, the most convenient and flexible way to express their needs and preferences is to input a piece of demand in the form of plain text and natural language, but currently no online travel platform can use effective technology to deal with such needs

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