Search content sorting method and device, storage medium and electronic equipment

Abstract

The invention relates to a search content sorting method and device, a storage medium and electronic equipment, and the method comprises the steps: determining a correlation score between each searchcontent corresponding to a search word and the search word through a pre-trained semantic correlation model; sorting the plurality of search contents according to the correlation score, wherein the training process of the semantic correlation model comprises the following steps: pre-training a language model through a plurality of search term samples and a first search content sample determined according to historical operation behaviors of a user for a plurality of search contents corresponding to each search term sample; and finely adjusting the pre-trained language model through the plurality of search term samples and two second search content samples corresponding to each search term sample, wherein the second search content samples are attached with tags used for representing whetherthe search content samples are related to the search term samples or not. According to the method, the correlation score of the search content can be determined through the pre-trained and fine-tunedsemantic correlation model, the application range of the semantic correlation model is widened, and the annotation cost is reduced.

Description

technical field [0001] The present disclosure relates to the technical field of search, and in particular, to a search content sorting method, device, storage medium and electronic equipment. Background technique [0002] The search platform can recommend several search results (hereinafter referred to as Document) to the user according to the keywords entered by the user (hereinafter referred to as Query). The search results need to be displayed to the user in the itinerary search result list after sorting. Therefore, the accuracy of the search result sorting directly affects the performance of the platform. Among them, text semantic relevance is one of the core factors in ranking, which is directly linked to the search experience. The purpose of judging the semantic relevance of text is to calculate the degree of correlation between the search term and the search content, that is, to judge whether the search content meets the user's search needs. It is one of the functio...

AI Technical Summary

Problems solved by technology

[0003] The main purpose of the present disclosure is to provide a search content sorting method, device, storage medium and electronic equipment to solve the technical problem in the related art that the application range of the correlation model is small and the labeling cost is high

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