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A smart recommendation system and method for urban scenic spots
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A recommendation system and scenic spot technology, applied in the field of big data, can solve the problems of exposing privacy, failing to protect user privacy and security, wasting time, etc., and achieve the effect of protecting privacy and security
Active Publication Date: 2021-06-25
ZHEJIANG LISHI TECH
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Problems solved by technology
[0002] With the gradual growth of my country's GDP, more and more people choose to go out to travel and relax, so the tourism industry is developing very rapidly. At present, tourism has become an important part of the tertiary industry, but with the increase in the number of tourists , stampede incidents appear in many travel scenes, most of which are caused by the large number of people playing, and within a limited time, users cannot match the corresponding game strategy according to their hobbies, so usually Waste a lot of time in the scenic area;
[0003] Now many platforms have discovered the scenic spot recommendation system, but the existing system cannot recommend the scenic spot that the user is interested in to the user in a personalized way. , in the patent No. CN201510517966.7, according to the user's identity information, it provides the user with a tailor-made best recommended route that is most suitable for the user to browse the scenic spot, which basically solves the problem of the user's tour route, but when customizing for the user At the same time, it also exposes the user's privacy and cannot protect the user's privacy;
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Embodiment 1
[0071] Embodiment 1: The number of comment clips watched by the user is 5. Among these 5 comments, the set of feature words such as particularly exciting, very pleasant, not fun, and too boring appearing in different word frequencies in the comment clips is W={3, 2,2,1}, the second modal particles expressed by different word frequencies in the comment segment are: special, very, not, too, the collection of the second modal particle word frequency is Y={5,4,3,2} , the frequency of occurrence of different expressions in the comment segment is B={6,8,3,1};
[0072] According to the formula:
[0073]
[0074]
[0075]
[0076]
[0077] Wherein, Z is the total probability times that different mood words occur; C i is the feature word as stimulus, S i is a characteristic word for soothing, A i Is that the characteristic word is quiet, C represents the frequency that the stimulus characteristic word occurs, S represents the frequency that the soothing characteristic wo...
Embodiment 2
[0079] Embodiment 2: In step S3, the set of items that the user wants to play in the scenic spot is X={x 1 ,x 2 ,x 3 ,x 4}, the number of people queuing up for each scenic spot is R={15,20,24,3}, each batch of visitors spends 20 minutes at different scenic spots, and the number of each batch of visitors is 10 people. The resulting error time is 5 minutes;
[0080] According to the formula:
[0081] G 1 =(15 / 10)·20+5=25min;
[0082] G 2 =(20 / 10)·20+5=45min;
[0083] G 3 =(24 / 10)·20+5=45min;
[0084] G 4 =(3 / 10)·20+5=5min;
[0085] G 4 1 2 =G 3
[0086] After the above calculation, it can be obtained that the user can go to the fourth scenic spot first, and then go to the first scenic spot after 20 minutes of playing, and then go to the second or fourth scenic spot after 20 minutes of playing.
[0087] Among them: G i Indicates the total visiting time of the visitor, the user can i+1 -G i Rush to the location of the scenic spot in the next scenic spot within a ...
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Abstract
The invention relates to the field of big data technology, and specifically discloses a smart recommendation system and method for urban scenic spots. The system can basically determine the nature of the user's play according to the nature of the user's travel and the browser search record, and can click on and observe the comments in the user's comments. Extract feature words, feature expressions, and feature-related words from the information, and reasonably avoid queuing according to the user's hobbies, and arrange the time reasonably according to the user's hobbies. The invention is scientific and reasonable, and safe and convenient to use. For each game item, the user's face is used to judge whether the user is enjoying the game, and combined with the user's score, the arrangement is scored, so that users with the same game nature can use it. The user's ratings or comments are used to play, and through the feature vector words in the comments, the user's hobbies can be learned, so that the user can enjoy playing in the scenic spot.
Description
technical field [0001] The invention relates to the field of big data technology, in particular to a smart recommendation system and method for urban scenic spots. Background technique [0002] With the gradual growth of my country's GDP, more and more people choose to go out to travel and relax, so the tourism industry is developing very rapidly. At present, tourism has become an important part of the tertiary industry, but with the increase in the number of tourists , stampede incidents appear in many travel scenes, most of which are caused by the large number of people playing, and within a limited time, users cannot match the corresponding game strategy according to their hobbies, so usually Waste a lot of time in the scenic area; [0003] Now many platforms have discovered the scenic spot recommendation system, but the existing system cannot recommend the scenic spot that the user is interested in to the user in a personalized way. , in the patent No. CN201510517966.7, ...
Claims
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