• Title/Summary/Keyword: Green Knight

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A Comparative Study of Structure and Theme in Beowulf and Sir Gawain and the Green Knight

  • Yang, Hyun-Chul
    • English Language & Literature Teaching
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    • no.5
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    • pp.249-258
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    • 1999
  • This paper will discuss how the structure and theme develop and compare between the Beowulf and Sir Gawain and the Green Knight. Sir Gawain and the Green Knight is generally considered as the finest of the English romances. The striking feature of this poem is its tight and organized structure, whereas most of the romances are loose in structure. This poem is composed of four fits containing traditional elements of romance: the Beheading Game; the Temptation and Hunting; the Exchange of Winnings; Returning. This process is linked together systematically, and as it goes on, certain external elements of romance come into view. There are heroic ideal, Christian humiliation and chastity, so the two themes or motifs are combined to produce a work of impressive organic unity.

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Analysis Method Study of Film Text using Word Vectors of Language Model (언어모델의 단어벡터를 이용한 영화 텍스트 분석 기법 연구)

  • Kwangho Ko;Juryeon Paik
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.6
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    • pp.703-708
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    • 2024
  • LSTM, a deep learning technique for building language models, can be easily trained on systems with small computing resources, unlike large language models. In this paper, we propose a convergent technique to train LSTM-based language models on small-scale texts and perform objective semantic and relational analysis on the main topic words of the text using the word vectors of the vocabulary comprising the text. Using the word vectors of a small language model trained on the English script of the 2021 movie "Green Knight" directed by David Lowery as a text, we proposed a technique that can analyze the meaning and relationship of the main topic words. Through the similarity operation of the word vector, the meaning and symbolism of each theme word can be objectively analyzed with the similarity scores between the words. The relationship between each theme word can be intuitively recognized by displaying the dimensionality-reduced two-dimensional word vector. By using a small-scale language model of the LSTM method, we proposed a method to analyze complex texts using word vectors while minimizing the cost of learning.