The Research And Implementation Of Travel Strategy Personalized Recommendation Technology Based On Text Mining

With the rapid development of information technology and tourism,the Internet has penetrated into the tourism industry.The importance of tourism literature in the tourism industry is also growing.The current numbers of travel documents in the Internet is growing at an exponential rate,and how to find a suitable documentary in a massive travel document to meet individual travel needs has become a problem.The emergence of personalized recommendation technology can effectively solve this problem,it can recommend to the user in line with the personalized needs of the travel document.Content-based recommendation technology has been widely used in a number of recommended technologies.The recommendation technology builds user description file by.The purpose of this paper is to propose an idea of travel document recommendation based on the content and theme solve the problem of the number of tourism documents which is large and indescribable,and propose a kind of LDA algorithm combined with the time influence factor in analyzing user's behavior.To help users quickly and accurately find suitable travel document from the mass travel literature,automatically recommend travel documentary which is useful to the user.This paper focus on the personalized recommendation techniques of tourism documents,and makes recommendations based on content and subject characteristics of a large number of tourist documents that have been crawled.Firstly,the theme model is used to analyze and calculate the contents,topics and keywords of tourism documents.At the same time,it analyzes the user's individual needs by LDA algorithm with.It takes full consideration of the Ebbinghaus forgetting curve when analyzing user's interest changes,and combine time-factor with LDA theme model when analyzing the user's historical content.Finally,it produces tourism documents recommendation after calculating the matching ratio of the tourism records and the user's interest model,get the personalized recommendation of travel document based on the use of content and theme characteristics of the recommended method.In this paper,we propose a method based on content and theme feature,which can help users to obtain the travel document which is easy to meet their own needs from a large number of travel documents.In this paper,we propose a LDA algorithm based on time influence factor to fully exploit the content that users may be interested in.Users do not need to spend time to find travel documents and save a lot of time and energy.The personalized recommendation system of tourism document is based on the individual recommendation and theme model.Firstly,the system requirements are analyzed.Secondly,the function and database of the system are designed in detail.Finally,some functions of the system are realized by using object-oriented programming technology,to provide users with tourist attractions recommending services.