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Text genre classification research

Authors: Zhijuan Xu; Lizhen Liu; Wei Song 0010; Chao Du;

Text genre classification research

Abstract

Essays in different text genres have different ideas and writing method. Prediction the text genres firstly will help get a better accuracy when predicting the success of literary or finding the beautiful words and sentences in the essay. And it will help set a different standard for different text genres when scoring the writing by computer. Words and structure can be effective in discriminating text genres. Narration and description has a difference in the words they use and the structure, we can separate them by analyze the difference. In this paper we find a method to separate the essay in different text genres by computer. We analyze the most effective features for distinguish genres. And discussed how to get a better result for genres classification. Finally, the f value reached 80% in our experiment.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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