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Algorithm for collaboratively filtering agricultural materials on basis of time and region granularity

A collaborative filtering algorithm and regional granularity technology, applied in the field of personalized services, can solve the problems of low prediction accuracy and large product scoring matrix, and achieve the effect of improving accuracy

Inactive Publication Date: 2016-04-20
无锡中科富创科技孵化有限公司 +2
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AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the defects that the existing collaborative filtering algorithm has low prediction accuracy in the field of agricultural materials and the user product rating matrix is ​​too large when calculating the similarity, and provides a collaborative filtering algorithm for agricultural materials based on time and regional granularity

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  • Algorithm for collaboratively filtering agricultural materials on basis of time and region granularity
  • Algorithm for collaboratively filtering agricultural materials on basis of time and region granularity
  • Algorithm for collaboratively filtering agricultural materials on basis of time and region granularity

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Embodiment Construction

[0020] The present invention will be further described below in conjunction with specific drawings and embodiments.

[0021] The collaborative filtering algorithm for agricultural materials based on time and regional granularity includes the following steps:

[0022] Step S1, time and region granularity division, according to the agricultural law, divide the national annual data into M*N granularity; that is to establish the time and regional granularity matrix A based on the existing survey results of agricultural statistical law m*n ;

[0023] Step S2, collect user behavior data for K years, divide the collected user behavior data into K parts according to the data year, and divide each part of data into m*n granularity according to time and geographical granularity; in this way, the collected The incoming user behavior data is divided into K*m*n granularities according to the annual, time, and regional granularity matrix;

[0024] Step S3, according to the divided data, e...

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Abstract

The invention provides an algorithm for collaboratively filtering agricultural materials on the basis of time and region granularity. The algorithm includes steps of building time and region granularity matrixes by the aid of existing agricultural statistical law research results; acquiring user behavior data; partitioning the acquired user behavior data according to the time and region granularity matrixes; building user commodity score matrixes of the time and region granularity where users are located; computing user similarity according to the user commodity score matrixes; finding out the most similar N users and recommending the agricultural materials to the current users on the basis of interest of the most similar N users. Compared with the traditional algorithm for collaboratively filtering agricultural materials on the basis of users, the algorithm has the advantage that the shortcomings of low prediction accuracy of the existing algorithm for collaboratively filtering the agricultural materials and excessively huge user commodity score matrixes when similarity is computed at present can be overcome by the aid of the algorithm.

Description

technical field [0001] The invention relates to a personalized service technology in the field of artificial intelligence, specifically a collaborative filtering algorithm for agricultural materials based on time and regional granularity. Background technique [0002] In today's e-commerce, personalized service technology is often used to tap the potential needs of users and improve user experience. Collaborative filtering algorithm is one of the most successful and widely used algorithms in personalized service technology. Collaborative filtering algorithm is based on the past purchase behavior of a customer and the purchase behavior of the customer group with similar purchase behavior to recommend the customer whose "may like" Items", that is, to provide personalized information, products, and other recommendation services based on the preferences of the community. In the excavation of user's personalized needs, the calculation method of user similarity that needs to find...

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Application Information

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IPC IPC(8): G06Q30/02
CPCG06Q30/0253G06Q30/0255
Inventor 董恒孙丙宇王伟汪六三李文波
Owner 无锡中科富创科技孵化有限公司
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