Research On Information Extraction And Recommendation Algorithm Of Yunnan Tourism Recommendation System

In recent years,as people's living standards improve and daily work pressure increases,with the tourism industry more and more popular,the public demand to stimulate a large number of tourism network service companies in the market emerged.Through the observation found that the current travel site on the user's recommendation is still the traditional recommendation of the main recommendation to the user to the higher heat attractions or do based on collaborative filtering recommendations,but these are clearly not in line with the actual situation of tourism in Yunnan Province and Unable to meet the needs of users.Travel sites have a large number of users published attractions evaluation and travel information,people will visit this information for reference before,but a lot of information browsing will also cause trouble,this article will effectively use these text information and combined with Yunnan Seasonal factors,the attractions of the heat factor for the user to make tourism in Yunnan Province personalized recommendation system.In this paper,two recommended algorithms are proposed for tourism.The first is the recommended algorithm based on the content of the site under the cold start condition of the system.The evaluation text of the root scenic spot is automatically extracted and then clustered for all the attractions.Attractions of the various categories of artificial labeling attributes,users enter the system after the manual selection of properties,the system according to the property category,real-time season and the attractions of the heat for the user recommended;And the other is a recommendation algorithm of scenic association rules based on travel document information.Based on the analysis of the user interaction data,the interest degree and the degree of recognition of the visitors are obtained.On this basis,the connotations of the spots in the tourist literature are used to form the collection of attractions that the users have arrived,and the association rules algorithm is used to excavate The potential model,the formation of rules,as the basis for the recommendation of the attractions to meet the needs of different groups to achieve a personalized service.