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体裁分析日益受到学界关注,“自上而下”的语步分析是其主流方法。语篇瓦片叠压(Text Tiling)技术已在文献检索、自动摘要等文本分析领域得到运用,可用来对说明性文本和学术论文等进行子话题(VBDU)自动、批量切分,与人工切分达到了很好的一致性,也和语步方法在语篇组织整体模式分析方面相一致。语篇瓦片叠压程序Python版本主要参数均可进行个性化设置,以满足不同文本类型、不同研究目的的需要。语篇瓦片叠压程序可分析书面语和口语,对理想文本的要求是:文本文件,英语语言,说明文本/科学杂志文章/学术论文/非文学文本,无(小)标题,文本长度300字以上、包含多个段落等。语篇瓦片叠压技术可尝试作为“自下而上”的体裁分析法,可以和语步方法相结合或作为其有益的补充。
Genre analysis is increasingly concerned by the academic community, “top-down ” step by step analysis is the mainstream method. Text Tiling technology has been used in text analysis such as document retrieval and automatic summarization. It can be used to automatically and batch sub-topics (VBDU), such as descriptive texts and academic papers, Points reached a very good consistency, but also with the step-by-step approach to the discourse analysis of the overall model consistent. Text Tile Stacking Program Python version of the main parameters can be personalized settings to meet different text types, different research purposes. Textual Tile Stacking Program Analyzes written and spoken language. The requirements for ideal text are: text file, English language, explanatory text / scientific journal article / scholarly thesis / non-literary text, no (small) title, text length 300 words Above, contains multiple paragraphs and so on. Discourse tile overlay technology can be used as a “bottom-up” genre analysis, which can be combined with or as a helpful complement to the step-by-step approach.