Loading and unloading point recommendation method and device based on graph neural network
A neural network and recommendation method technology, applied in the field of loading and unloading point recommendation, can solve problems such as affecting the driver's user experience, poor unloading point recommendation effect, etc., to improve the experience and improve the accuracy.
Active Publication Date: 2022-03-01
深圳依时货拉拉科技有限公司
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With the development of word embedding technology, many methods embed the feature information describing interest points and loading and unloading points as the representation vectors of interest points and loading and unloading points, and capture the characteristics of interest points and loading and unloading points. However, the unloading point of this method Point recommendation is not effective, affecting driver and user experience
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[0052] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.
[0053] The inventor considers that the current method of recommending loading and unloading points does not capture the collaborative information in the interaction graph of the loading and unloading points of interest points, and the generated representation vector is not enough to capture the influence of collaborative filtering; Considering physical location information, the impact of location information is not captured. In order to improve the recommendation accuracy, this application uses graph neural network technology to recommend loading and unloading points. The graph neural net...
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The invention relates to a loading and unloading point recommendation method and device based on a graph neural network, computer equipment and a storage medium. The method comprises the following steps: constructing an interest point diagram based on geographic position information, a loading and unloading point diagram based on geographic position information and an interest point loading and unloading point interaction diagram; fusing the interest point characterization vector based on the interaction information and the interest point characterization vector based on the geographic position information to obtain an interest point characterization vector fusing the interaction information and the geographic position information; fusing the loading and unloading point characterization vector based on the interaction information and the loading and unloading point characterization vector based on the geographic position information to obtain a loading and unloading point characterization vector fusing the interaction information and the geographic position information; and the interest point representation vector fusing the interaction information and the geographic position information and the loading and unloading point representation vector fusing the interaction information and the geographic position information are input into the graph neural network for recommendation, so that the accuracy and the reliability of the recommendation of the loading and unloading points can be greatly improved, and the method is more intelligent, efficient, reasonable and wide in application range.
Description
technical field [0001] The present application relates to the field of loading and unloading point recommendation, in particular to a graph neural network-based loading and unloading point recommendation method, device, computer equipment and storage medium. Background technique [0002] Nowadays, users place orders on the APP platform, and the point of interest (POI) placed by some order users is far away from the actual loading and unloading point of the user. The driver’s user experience is poor. In order to improve the efficiency of the driver’s cargo meeting, reduce the cost of meeting, improve the experience of drivers and users on the platform, and allow more drivers and users to choose and save on the platform, a smarter method based on the user’s order of interest is needed. Recommended solution for loading and unloading points. [0003] Collaborative filtering is a method widely used in recommendation systems. Its basic idea is to find other points of interest sim...
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IPC IPC(8): G06Q10/04G06N3/04G06N3/08G06Q10/08
CPCG06Q10/04G06Q10/08355G06N3/04G06N3/08
Inventor 赵斌伟廖泽平沈永新杨晨强成仓石立臣
Owner 深圳依时货拉拉科技有限公司