I am working in a text classification problem involving a dataset that contains a vocabulary of 250,000 tokens (words)

Apart from removing stop words and performing stemming, which other simple approaches could be used to reduce dimensionality of this problem?

Can anyone suggest good papers/readings on this subject?

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