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ELSA: a multilingual document summarization algorithm based on frequent itemsets and latent semantic analysis

机译:ELSA:一种基于频繁项目集和潜在语义分析的多语言文献摘要算法

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摘要

"You shall know a word by the company it keeps" is perhaps the most famous quotation attributed to J. R. Firth [1]. Searching for ways to automate natural language understanding (NLU), statistical natural language processing prevailed in the field for many decades. This was founded on the frequentist or empiricist traditions of British (corpus) linguistics, led by Firth, Michael A. K. Halliday, and John Sinclair. Contemporary computational linguistics looks at representing natural language as calculated frequencies of co-occuring terms and collocation within a metric space.
机译:“你应该通过它保持的公司知道一个词”也许是最着名的报价归因于J. R. Firth [1]。搜索自动化自然语言理解的方法(NLU),统计自然语言处理数十年来在该领域占上风。这是由英国(语料库)语言学的常见或经验主义传统,由Firth,Michael A. K. Halliday和John Sinclair领导。当代计算语言学看起来代表自然语言,作为公制空间内共同发生术语和搭配的计算频率。

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