A Personalized Travel Travel Recommendation Method Based on Probabilistic Graph Model
A probabilistic graph model and recommendation method technology, applied in the direction of instruments, data processing applications, data mining, etc., can solve the problems of sparse data, not involving tourist locations, uneven data distribution, etc., and achieve the effect of improving accuracy
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[0059] Such as figure 1 As shown, a personalized travel recommendation method based on a probabilistic graphical model includes the following steps:
[0060]S1: Travel note topic initialization: Segment the travel note articles, adopt the standard article topic model, and obtain the topic distribution of each travel note and the topic distribution of each word through Gibbs sampling, and use the calculated topic distribution to compare travel notes and The relevant parameters of word gamma distribution are assigned. In addition, the relevant parameters of user preferences and location hidden features are assigned initial values with random numbers;
[0061] S2: For each word in each travel note, calculate the logarithmic value of the word frequency relationship through the distribution of word topics and article topics, and update each travel note and the shape parameter in the gamma distribution parameters of the words in the travel note;
[0062] S3: For each travel note ...
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