| With the advent of the Big Data era,people are prompted to enter a situation of information overload.How users can filter out the information they need from a large number of information,whether these screening work can be done by a computer or not,Whether to truly meet the needs of users,in order to solve these problems,recommended system came into being.The recommendation system is an important way to solve the information overload problem,which can meet the individual needs of people.When users browse the website,they will record the search or click behavior.The recommendation system will excavate according to the data and recommend the information they need for each user.And then the tourism information recommendation system is more complex.With the rapid development of information technology,the explosive growth of tourism information makes it more and more difficult for travelers to obtain travel information that meets their needs in the face of massive tourism information resources.Second,People's living standards continue to improve,people's tourism consumption concept is also becoming more mature and personalized,and now the tourism recommendation system has been difficult to meet the growing tourist demand for travelers.Therefore,according to the characteristics and personalities of different travelers,personalized recommendation of travel information has been especially necessary.The thesis firstly analyzes the concept,application and current situation of tourism information system by sorting out relevant literature of domestic and overseas tourism information recommendation system in recent ten years,and puts emphasis on the recommendation algorithm and the application of key technologies in tourism recommendation system Summarized the complexity and particularity of the application of tourism recommendation system,put forward a reliable solution to its complexity and particularity,and designed a highly recommended system for the tourism industry. |
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