The invention relates to a text label extracting method. The text label extracting method comprises the following steps: category prediction is performed on a to-be-extracted text through a text categorization model, and a target category of the text is obtained; topic prediction is performed on the to-be-extracted text through a topic clustering model, and a predicted topic is obtained; if the predicted topic is in a default topic set, a target topic corresponding to the predicted topic is acquired, keyword extraction is performed on the to-be-extracted text, target keywords of the text are obtained, and the target category, the target topic and the target keywords are taken as labels of the text. The text labels have different levels to meet multi-granularity retrieval requirements, and multi-granularity recommended articles can be provided according to different labels. Besides, the invention provides a text label extracting device.