文本的词法简化的Web扩展

Karan Bhat, Vaibhavi Ghumare, Siddhesh Khadake, H. Gadade
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引用次数: 0

摘要

词汇简化是指用更容易理解的文本代替句子中的复杂单词,同时保留原文的上下文和语法,使整个句子更容易理解的过程。最近所有涉及词汇简化的工作都依赖于无监督任务来学习复杂单词的更简单替代。但这些研究的缺点是,它们提供了更简单的单词,而没有考虑句子中复杂单词的上下文。在本文中,我们提出了一个基于上下文学习的词汇简化器。我们应用了预训练的表示模型BERT。它是一个非常强大的工具,可以在前进和后退的方向上利用句子的更广泛的语境。我们还从微妙列表中提取了词频指示器,以产生语义和语法上更正确的结果。我们还添加了一个web扩展,用于简化网页上的文本,它从用户那里获取输入,在服务器端处理文本,并在计算结束后返回结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web Extension for Lexical Simplification of Text
Lexical simplification means the process of providing alternatives to the complex words in the sentence with texts that are much more simpler to understand, while also preserving the context and grammar of the original text to make the whole sentence more easier to understand. All of the recent work involving lexical simplification relies on unsupervised tasks to learn simpler alternatives of complex words. But the drawback of most of these researches has been the fact that they provide simpler words without taking the context of the complex word in the sentence in account. In this paper, we are proposing a lexical simplifier which is based on contextual learnings from the sentence. We have applied the pre-trained representation model, BERT. It is a very powerful tool which can make use of the wider context of the sentence in both forward and backward direction. We have also taken the word frequency indicator from the Subtlex list, to produce results that will be more correct both semantically and grammatically. We have also added a web extension for the simplification of the text on the webpage, which takes the input from the user, processes the text on the server end, and gives the result in return after computation is over.
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