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'Shakespeare in the Vectorian Age' - An evaluation of different word embeddings and NLP parameters for the detection of Shakespeare quotes

机译:'维多利亚时代的莎士比亚' - 对NLP参数中的不同词嵌入的评估,用于检测莎士比亚报价

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In this paper we describe an approach for the computer-aided identification of Shakespearean in-tertextuality in a corpus of contemporary fiction. We present the Vectorian, which is a framework that implements different word embeddings and various NLP parameters. The Vectorian works like a search engine, i.e. a Shakespearean phrase can be entered as a query, the underlying collection of fiction books is then searched for the phrase and the passages that are likely to contain the phrase, either verbatim or as a paraphrase, are presented in a ranked results list. While the Vectorian can be used via a GUI, in which many different parameters can be set and combined manually, in this paper we present an ablation study that automatically evaluates different embedding and NLP parameter combinations against a ground truth. We investigate the behavior of different parameters during the evaluation and discuss how our results may be used for future studies on the detection of Shakespearean intertextuality.
机译:在本文中,我们描述了一种在当代小说中的计算机辅助识别莎士比亚的智典素内的方法。我们介绍了矢量人,这是一种实现不同单词嵌入和各种NLP参数的框架。 vectorian就像一个搜索引擎,即莎士比亚短语可以作为查询输入,然后搜索小说书籍的底层集合,并且可能包含包含短语,逐字或释义的段落的短语和段落是呈现在排名的结果列表中。虽然矢量是通过GUI使用的,但是在该纸张中可以手动设置和组合许多不同的参数,在本文中,我们介绍了一种消融研究,它会自动评估不同的嵌入和NLP参数组合对基础事实。我们调查评估过程中不同参数的行为,并讨论我们的结果如何用于对未来关于检测莎士比亚互文性的研究。

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