Commodity labeling method suitable for electronic commerce Chinese website

Abstract

A commodity labeling method suitable for an electronic commerce Chinese website includes the step of building a word segmentation lexicon, the step of collecting labels and the step of marking commodities with the labels. According to the step of building the word segmentation lexicon, based on frequency statistics, in different commodity descriptions, of all commodity key words in the electronic commerce Chinese website, the commodity key words with the frequency larger than three are reserved, and the key words with the number of Chinese characters of the commodity key words smaller than or equal to five are screened from the commodity key words to serve as lexicon data. According to the step of collecting the labels, based on the built word segmentation lexicon, word segmentation processing is carried out on all commodity names in the electronic commerce Chinese website through a reverse maximum matching word segmentation algorithm, after word segmentation processing is carried out through the reverse maximum matching word segmentation algorithm, the last word formed by word segmentation processing of each commodity is selected as the commodity label of the commodity, and finally all the labels form a label data set. According to the step of marking the commodities with the labels, relations between commodity attributes and the labels are found by using a text mining algorithm.

Description

technical field [0001] The invention belongs to the field of computer internet, and in particular relates to a method suitable for labeling commodities on e-commerce Chinese websites. Background technique [0002] On e-commerce Chinese websites, when users use keywords to search for products, they usually directly retrieve the basic information of the products. information, but still can not avoid the emergence of two types of problems: one is the problem of product information cheating, in order to provide the exposure rate and frequency of appearance of their products in the product search process, the merchants make the released products eye-catching, so that product buyers More products can be searched, and they abuse brand names or keywords that are not related to the product when describing the product, so that product buyers cannot accurately find the product they need; the second is that the product information is not comprehensive The problem is that merchants omit...

AI Technical Summary

Problems solved by technology

[0002] On e-commerce Chinese websites, when users use keywords to search for products, they usually directly retrieve the basic information of the products. information, but still can not avoid the emergence of two types of problems: one is the problem of product information cheating, in order to provide the exposure rate and frequency of appearance of their products in the product search process, the merchants make the released products eye-catching, so that product buyers More products can be searched, and they abuse brand names or keywords that are not related to the product when describing the product, so that product buyers cannot accurately find the product they need; the second is that the product information is not comprehensive The problem is that merchants omit key information about product descriptions when describing products, including missing important information such as product titles, pictures, and descriptions. The lack of information will cause the website to fail to return more relevant product search results when users search for products.

[0003] For the problem of merchants cheating on product information, e-commerce websites usually set up rules to solve the problem, and lower the rights of those cheating products that do not meet the rules. However, there are certain defects in the rules, and strict rules may lead to the reduction of rights of non-cheating products; Loose rules may make the anti-cheating effect not obvious enough; in order to solve the problem of incomplete information filled by merchants, in order to ensure that as many related products as possible are recalled, e-commerce websites choose to expand the retrieval range of commodity information at the expense of retrieval quality, That is, multiple product information fields are matched, and sometimes even fields with a large amount of data but poor quality such as "product description" are selected. Although more products can be recalled in this way, the recalled products cannot be recalled. Satisfied users, resulting in significant traffic loss

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