Personalized scenic spot recommendation method and device based on knowledge graph and long-term and short-term preferences of user

A knowledge map and recommendation method technology, applied in the field of personalized scenic spot recommendation, can solve the problems of low recommendation accuracy and low degree of personalization of recommendation results, and achieve the effect of improving accuracy

Active Publication Date: 2019-09-27
GUILIN UNIV OF ELECTRONIC TECH
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Problems solved by technology

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a personalized scenic spot recommendation method and device based on knowledge

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  • Personalized scenic spot recommendation method and device based on knowledge graph and long-term and short-term preferences of user
  • Personalized scenic spot recommendation method and device based on knowledge graph and long-term and short-term preferences of user

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Embodiment Construction

[0041] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0042] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the compo...

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Abstract

The invention provides a personalized scenic spot recommendation method based on a knowledge graph and long and short-term preferences of a user. The method comprises the following steps: preprocessing a historical tourist scenic spot sequence of a tourist, and carrying out scenic spot-coding conversion; using node2vec to randomly walk to obtain a scenic spot sequence, and using Skip-gram model in word2vec to obtain feature vectors of tourists and scenic spots; adding bias to the feature vectors of the scenic spots to serve as input of a GRU network, and then utilizing the GRU network to train and output the potential vector of each scenic spot; allocating different weights to the scenic spots, multiplying the weight of each scenic spot by the potential vector of the scenic spot, accumulating to obtain the long-term preference of the current tourist, splicing the long-term preference of the current tourist and the current preference of the tourist, and multiplying the spliced preference by the weights to obtain a final vector; and performing dot product operation on the final vector and the current preference of the tourist to obtain an estimated score of the scenic spot, performing normalization processing on the estimated score of the scenic spot to obtain a prediction probability of each scenic spot, and taking scenic spots corresponding to the former K scores to obtain a top_k scenic spot recommendation list.

Description

technical field [0001] The present invention relates to technical fields such as intelligent recommendation, in particular to a personalized scenic spot recommendation method and device based on knowledge graphs and long-term and short-term preferences of users. Background technique [0002] With the improvement of the consumption level of the Chinese people, the people's demand for traveling is increasing day by day. According to relevant data, the number of people traveling is on the rise. Recommendation system technology has also emerged, but most of the current recommendation systems cannot fully meet the individual needs of users. The specific reason is that the existing travel recommendation methods only construct user preference feature representations based on the user's historical visit location, so as to make personalized recommendations. However, the travel interests of users may change over time. Therefore, the existing scenic spot recommendation methods are d...

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Application Information

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IPC IPC(8): G06F16/36G06F16/9535G06Q50/14G06N3/04G06N3/08
CPCG06F16/367G06F16/9535G06Q50/14G06N3/08G06N3/048G06N3/045
Inventor 宾辰忠贾中浩古天龙常亮陈炜朱桂明
Owner GUILIN UNIV OF ELECTRONIC TECH
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