In the study of two similar literature masterpieces, A Dream in Red Mansions and The Story of Genji, garden planning, plant selection, aesthetic conception, descriptions about gardens, religious elements, architectura...In the study of two similar literature masterpieces, A Dream in Red Mansions and The Story of Genji, garden planning, plant selection, aesthetic conception, descriptions about gardens, religious elements, architectural decorations and touring ways in both works were comparatively analyzed. Differences in geological conditions, social backgrounds, aesthetic traditions and religious beliefs led to different development trends of gardens in China and Japan. Chinese gardens were largely influenced by humanistic and cultural elements, famous for poetic and artistic conceptions, while Japanese gardens covered by religious colors, and most of its private gardens built with Buddhist preferences just like temple gardens. Chinese gardens valued the application of diversified plant species, while Japanese gardens favored evergreen plants, not flowers. Chinese preferred sightseeing in scenery, but Japanese preferred meditation, which means that, there were different touring ways in two countries. In conclusion, social and cultural differences contributed to the literati garden with profound humanity background in China and the Buddhist garden of religious colors in Japan.展开更多
In this paper, visualization of special features in “The Tale of Genji”, which is a typical Japanese classical literature, is studied by text mining the auxiliary verbs and examining the similarity in the sentence s...In this paper, visualization of special features in “The Tale of Genji”, which is a typical Japanese classical literature, is studied by text mining the auxiliary verbs and examining the similarity in the sentence style by the correspondence analysis with clustering. The result shows that the text mining error in the number of auxiliary verbs can be as small as 15%. The extracted feature in this study supports the multiple authors of “The Tale of Genji”, which agrees well with the result by Murakami and Imanishi [1]. It is also found that extracted features are robust to the text mining error, which suggests that the classification error is less affected by the text mining error and the possible use of this technique for further statistical study in classical literatures.展开更多
文摘In the study of two similar literature masterpieces, A Dream in Red Mansions and The Story of Genji, garden planning, plant selection, aesthetic conception, descriptions about gardens, religious elements, architectural decorations and touring ways in both works were comparatively analyzed. Differences in geological conditions, social backgrounds, aesthetic traditions and religious beliefs led to different development trends of gardens in China and Japan. Chinese gardens were largely influenced by humanistic and cultural elements, famous for poetic and artistic conceptions, while Japanese gardens covered by religious colors, and most of its private gardens built with Buddhist preferences just like temple gardens. Chinese gardens valued the application of diversified plant species, while Japanese gardens favored evergreen plants, not flowers. Chinese preferred sightseeing in scenery, but Japanese preferred meditation, which means that, there were different touring ways in two countries. In conclusion, social and cultural differences contributed to the literati garden with profound humanity background in China and the Buddhist garden of religious colors in Japan.
文摘In this paper, visualization of special features in “The Tale of Genji”, which is a typical Japanese classical literature, is studied by text mining the auxiliary verbs and examining the similarity in the sentence style by the correspondence analysis with clustering. The result shows that the text mining error in the number of auxiliary verbs can be as small as 15%. The extracted feature in this study supports the multiple authors of “The Tale of Genji”, which agrees well with the result by Murakami and Imanishi [1]. It is also found that extracted features are robust to the text mining error, which suggests that the classification error is less affected by the text mining error and the possible use of this technique for further statistical study in classical literatures.
