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Cold-chain logistic stowage intelligent recommendation method based on spectral cl9ustering

A technology of cold chain logistics and recommendation method, which is applied in the field of recommendation and can solve problems such as the large impact of sparsity in the scoring matrix

Inactive Publication Date: 2016-06-08
HUAIYIN INSTITUTE OF TECHNOLOGY
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AI Technical Summary

Problems solved by technology

[0006] Collaborative filtering algorithm has been widely used in the field of recommendation system and has achieved good recommendation results, but there are still problems such as being greatly affected by the sparsity of the scoring matrix.

Method used

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  • Cold-chain logistic stowage intelligent recommendation method based on spectral cl9ustering
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  • Cold-chain logistic stowage intelligent recommendation method based on spectral cl9ustering

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Embodiment Construction

[0025] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0026] as attached figure 1 Shown, the embodiment of the present invention carries out according to the following steps:

[0027] Step 1. Set the number of users in the cold chain logistics stowage system as M and the number of stowage routes as N, and establish a user set and the set of stowage routes ;

[0028] Step 2, set means user For stowage routes ratings of which, , ;Establish the user's scoring matrix for the loading route ;

[0029] Step 3, set ,in, ,and ;make means user with users the similarity of , Respectively represent the user and user For stowage routes ratings of which, ;like or One item is empty, that is, the loading route If there is an ungraded situation, then let , using Euclidean distance to calculate user similarity , get the user similarity matrix ;

[0030] Step 4. Calculate...

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Abstract

The invention discloses a cold-chain logistic stowage intelligent recommendation method based on spectral clustering. Scores of users for a stowage line are conveyed through a cold chain for cold-chain logistic stowage intelligent recommending, a score matrix is built, the Euclidean distance is used for calculating the user similarity, a degree matrix is used for calculating a Laplacian matrix, feature vectors are obtained by calculating feature values of the orderly Laplacian matrix, a K-means algorithm is used for clustering the feature values to obtain a user group with the similar interesting stowage line, and a stowage line is recommended inside the user group with the similar interesting stowage line, so that cold-chain logistic stowage intelligent recommending is achieved, the cold-chain logistic vehicle non-load ratio is lowered, and the profit rate of cold-chain logistic transport vehicles is increased.

Description

technical field [0001] The invention belongs to the technical field of recommendation, in particular to an intelligent recommendation method for cold chain logistics distribution based on spectral clustering, which can be applied to a cold chain logistics distribution recommendation system. Background technique [0002] The recommendation system provides customized information and services that users may be interested in by comprehensively analyzing user preferences, habits, access records, purchase records and other information. It is widely used in e-commerce, online film and television, news advertisements and other fields. Such as Amazon shopping (Amazon), Taobao, Google advertising and so on. Collaborative filtering recommendation is one of the earliest and most successful techniques applied in the recommendation system. Its basic assumption is: if users have the same preferences in the past (for example, they have browsed or purchased the same books), then they will ha...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/08G06Q50/28G06K9/62
CPCG06Q10/083G06F18/2323G06F18/23213G06Q10/08
Inventor 李翔朱全银胡荣林周泓
Owner HUAIYIN INSTITUTE OF TECHNOLOGY
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