Method and device for determining association degree between food material nouns, equipment and medium

Abstract

The embodiment of the invention provides a method and device for determining the association degree between food material nouns, electronic equipment and a readable storage medium. The method comprises the steps: determining a legal jump probability of jumping from a first food material noun to a second food material noun under the condition of meeting legal path constraints according to a mappingrelationship between dishes and menus and a mapping relationship between the menus and the food material noun; according to a mapping relationship between the menu and the food material noun, determining an illegal jump probability that the first food material noun jumps to the second food material noun under the condition that an illegal path constraint is satisfied; and determining the association degree between the first food material noun and the second food material noun according to the legal jump probability and the illegal jump probability of jumping from the first food material nounto the second food material noun.

Description

technical field [0001] The embodiments of the present application relate to the technical field of data processing, and in particular to a method, device, electronic device, and readable storage medium for determining the degree of association between food nouns. Background technique [0002] With the development of e-commerce platforms, more and more dishes are displayed and sold through e-commerce platforms. In order to be able to display each dish in multiple dimensions to buyers and users, and to facilitate buyers to search for desired dishes more accurately, e-commerce platforms usually need to build knowledge graphs in the field of food to reflect the degree of correlation between nouns of ingredients. Such as synonym relationship, synonym relationship, and superior-subordinate relationship, etc., and labels can be set for similar food nouns based on the above-mentioned relationship, such as fish, chicken, eggs, fungi, etc. labels. [0003] In order to establish a kno...

AI Technical Summary

Problems solved by technology

However, the above method is highly dependent on the data source, and there are few professional data sources in the field of food, and the data type is single. Therefore, it is difficult to use the above method to build a knowledge map in the field of food, and it cannot reflect the degree of correlation between food nouns.

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