Research On Recommendation Algorithm Of Scenic Spots Based On Location Social Network

Travel,as a leisure way to relieve the pressure of life and work,has become an indispensable part of many people's lives.The recommendation of interesting places plays a key role in travel.There are two problems in the current travel recommendation process:community recommendation and interesting location recommendation abroad.In view of the above problems,we analyze the challenges and propose more reasonable and effective recommendation strategies based on the existing principles.This paper aims to complete the following tasks:Firstly,the current research status of interesting location recommendation algorithms at home and abroad is described,and the previous research methods of location recommendation and their advantages and disadvantages are discussed to provide reliable theoretical support for the following research.Secondly,this paper proposes a community interesting location recommendation algorithm,the core idea of which is to first borrow the tf-idf algorithm idea to obtain the evaluation of interesting location by individuals in the community,and then to obtain the evaluation of interesting location by the whole community through the aggregation strategy of weighted fusion of everyone's evaluation.In the calculation of the weight of each person in the community,it is necessary to observe the importance of the character in the community,and introduce the two factors of the social relationship of the character and the degree of similarity of the character,to weight the character in the community and get the evaluation of the interesting position of the whole community,so as to form the community recommendation.Finally,a foreign interesting location recommendation algorithm is proposed.Thegeneral idea is to transform the problem of new location recommendation for characters into an evaluation problem.Then,according to the similarity degree of characters,the evaluation of interesting location for target characters is obtained.The specific implementation first uses the expert mechanism to calculate the collection of tourism experts in a certain kind of interesting location in a foreign city,then calculates the degree of similarity between tourism experts and tourists,and obtains tourists' evaluation of the recommended location according to the evaluation of tourism experts.The higher the evaluation,the more worthy the recommendation to tourists.