Sorting method and system for labels in network recommendation

Abstract

The invention discloses a sorting method for labels in network recommendation. The method comprises the steps of determining and obtaining keywords which possibly become labels for to-be-recommended content; acquiring network data of each keyword; classifying network data sources of the keywords and adding different weights to obtain a keyword statistics result; according to the statistics result, screening the keywords and taking the screened keywords as the labels of the to-be-recommended content; and according to the statistics result, sorting the obtained labels. The invention furthermore discloses a sorting system for the labels in the network recommendation. According to the sorting method and system for the labels in the network recommendation, the network data of the keywords is subjected to weighted calculation, so that the proper keywords capable of serving as the labels can be accurately obtained and the labels can be reasonably sorted through statistics calculation.

Description

technical field [0001] The invention relates to network information processing technology, in particular to a tag sorting method and system in network recommendation. Background technique [0002] With the development and popularization of Internet technology, the network has become one of the main means for people to obtain information. However, as network information becomes more and more abundant and complex, how to accurately obtain the information people want through the network has gradually become a difficult problem. . Usually, when the network makes recommendations, different labels are placed on the recommended content. For example, the labels of film and television works may include information such as film and television genre, director, and starring role. [0003] However, currently, the tags of audio-visual works in network recommendation are highly subjective, and there is no objective basis for the ranking of tags. For example: There are three leading actor...

AI Technical Summary

Problems solved by technology

[0003] However, the labels of audio-visual works in network recommendation are very subjective, and there is no objective basis for the ordering of labels.

For example: There are three leading actors in a film and television work, but there is currently no reasonable solution to whether these three leading actors should be tagged, or which leading actor should be ranked first.

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