Method and device for outputting information

Abstract

The embodiment of the invention discloses a method and a device for outputting information. A specific embodiment of the method comprises the steps of obtaining text information of a to-be-matched image; inputting the text information into a pre-trained classification model to obtain subject words of the text information; matching the text information with a preset entity list to obtain entity words of the text information; and obtaining a picture matched with the subject word and the entity word from a preset picture library and outputting the picture. According to the method, the related picture can be retrieved quickly and efficiently according to the text content.

Description

technical field [0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to methods and devices for outputting information. Background technique [0002] In the information age, data is becoming more and more important. With the explosive growth of data, the cost of quickly obtaining the data you want is getting higher and higher, especially for pictures that cannot be vividly described, it is more difficult to obtain. [0003] At present, most of the pictures accompanying articles on the market are directly obtained through manual search and screening, but this will consume a lot of human and financial resources, and it is not necessarily possible to get high-quality pictures. The main problems of existing methods are: (1) Partial subjectivity: For manual screening methods, different subjective biases often affect the picture configuration and the matching degree between text and pictures. (2) Limitations: Due to limited m...

AI Technical Summary

Problems solved by technology

With the explosive growth of data, the cost of quickly obtaining the data you want is getting higher and higher, especially for pictures that cannot be described vividly, it is more difficult to obtain

[0003] At present, most of the pictures for articles on the market are obtained directly through manual search and screening, but this will consume a lot of human and financial resources, and it is not necessarily possible to get high-quality pictures

The main problems of the existing methods are: (1) Partial subjectivity: For manual screening, different subjective biases often affect the picture configuration and the matching degree between text and pictures

(2) Limitation: Due to limited manpower, it is often impossible to retell all the texts

(3) Complicated and inefficient, manual retrieval of pictures for matching, high cost and low performance

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