Research Experiment on Multi-Model Comparison for Chinese Text Classification Tasks
This is an incremental study for researchers in natural language processing, as it applies existing methods to Chinese text data without introducing new techniques.
This paper tackled the problem of Chinese text classification by comparing three deep learning models (TextCNN, TextRNN, FastText) on the THUCNews dataset, but it did not report any concrete performance numbers or results in the abstract.
With the explosive growth of Chinese text data and advancements in natural language processing technologies, Chinese text classification has become one of the key techniques in fields such as information retrieval and sentiment analysis, attracting increasing attention. This paper conducts a comparative study on three deep learning models:TextCNN, TextRNN, and FastText.specifically for Chinese text classification tasks. By conducting experiments on the THUCNews dataset, the performance of these models is evaluated, and their applicability in different scenarios is discussed.