A Study of Chinese News Headline Classification Based on Keyword Feature Expansion

A Study of Chinese News Headline Classification Based on Keyword Feature Expansion

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Abstract Existing work generally classifies news headlines as a matter of short text classification.However, due to the strong domain nature and limited text length of news headlines, their classification results are usually determined Lip Balm by several specific keywords, which makes the traditional short text classification method ineffective.In this paper, we propose a new method to identify keywords in news headlines and expand their features from sentence level and word level respectively, and finally use convolutional neural networks Cat Treats (CNN) to extract and classify their features.The proposed model was tested on the Sogou News Corpus dataset and achieved 93.

42 $$%$$ % accuracy.