Knowledge based agricultural material commodity recommendation method

Abstract

The invention discloses a knowledge based agricultural material commodity recommendation method, and relates to the technical field of commodity personalized recommendation. The knowledge based agricultural material commodity recommendation method comprises the steps of analyzing user and commodity features by combining the problem background, and generating a case library structure according to the features; according to specific user information, judging whether a case corresponding to the user feature exists or not in the case library, and thus performing different operations on the case library; acquiring a commodity feature matched with the corresponding user feature from the case library, and generating an agricultural material commodity supposed to be recommended by combining the commodity information. Compared with a traditional agricultural material commodity recommendation method, the recommendation method provided by the invention solves a problem of cold start; the scientificity and effectiveness of agricultural material commodities are ensured based on actual requirements of users by combining agricultural production knowledge; the establishment of the case library enables the knowledge based recommendation to be more efficient.

Description

Technical field [0001] The invention relates to the technical field of commodity personalized recommendation, in particular to a knowledge-based method for recommending agricultural materials and commodities. Background technique [0002] Product personalized recommendation technology plays an important role in modern e-commerce. Demand and preference are two factors that affect consumers' purchase of goods, as well as two important aspects that should be considered in the recommendation method. Traditional agricultural product recommendation methods are mostly based on product recommendations and collaborative filtering recommendations, which require certain product sales records as support, and extract user preferences from these product sales records. In addition, due to the special nature of agricultural products—the inability to bring users a direct product experience when purchasing, this feature makes the traditional method of only considering user preferences for agricul...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies of the traditional methods for recommending agricultural materials and commodities, and provide a knowledge-based method for recommending agricultural materials and commodities. Affect the needs and preferences of users to choose products, focusing on user needs and ignoring user preferences

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