Research On Personalized Recommendation Algorithm For Intelligent Travel Service Robots

Service robots are the most suitable type for people's lives in the field of robots.They appear to replace people in the service industry.As one of service robot,the tourism service robot replaces the traditional tourism service industry practitioners to provide personalized travel services to users.In the traditional tourism service industry,service staff always provide users with tourism services that maximize their benefits.This is incompatible with the era of personalization,which makes people's tourism experience very poor,and also causes waste of human resources in the tourism service industry.In order to solve these problems,smart travel service robots have emerged with the development of artificial intelligence and service robots.It appears to provide people with personalized travel services,improve people's travel experience,and thus continue to promote the development of the tourism industry.In the process of traveling,many aspects require smart travel service robots to provide services such as diet,accommodation,scenic spots,etc.,among which the choice of attractions and the planning of visiting routes are the most troublesome problems for tourists.Therefore,this paper mainly studies the personalized recommendation algorithm for intelligent travel service robots and embeds them into the travel service robot.In order to realize personalized service,we must first obtain the personalized preferences of each user,which is obtained from historical travel information in this article.After obtaining the personalized preference of the people,by calculating the matching degree of the user with the attraction or the route,the recommendation with the highest matching degree can be used to realize the function of the personalized service recommendation service and the personalized travel route recommendation service of the tourism service robot.The main research work of this paper is as follows:(1)A fixed intelligent travel service robot is designed to realize the personalized service recommendation service and personalized travel route recommendation service function for users.(2)In order to obtain the historical behavior data of users,a construction method of user travel route database based on tourism knowledge map is designed.(3)For the personalized service recommendation service function of the intelligent travel service robot,two methods for recommending personalized attractions are proposed.The first is based on the unsupervised multiple hidden semantic trajectory mining model MLS2 vec,for the reason that the recommendation result of the unsupervised method is not good,then a multi-granular mining model based on supervised learning is proposed to improve the recommended service quality of intelligent tourism service robot.(4)For the personalized travel route recommendation service function of the intelligent travel service robot,the method similar to MLS2 vec is first adopted to obtain the individualized preference of each person,then a PrefixSpan-based travel route generation method is proposed.Based on the user's preferences and the characteristics of the generated route,the personalized travel route recommendation service is performed on the user according to the degree of matching.