• Journal of the Korean Institute of Landscape Architecture
• /
• v.37 no.1
• /
• pp.110-119
• /
• 2009

Sosang Pal-Kyung(瀟湘八景), which originated in China and means eight scenes of So River and Sang River, greatly influenced the poems and the pictures in East Asia for a long time and became a cultural phenomenon leading the stereotype of the traditional landscapes in Korea and Japan. Studies on 'Kyung(a scene)' such as 'Pal-Kyung(八景)', have been made continuously until now, but there are no results of a study intensively focusing on the meaning and the form of Sosang Pal-Kyung, which is the origin of the domestic Pal-Kyung culture. The goal of this study is to investigate the typical form observed in Sosang Pal-Kyung-Ga(瀟湘八景歌) and Sosang Pal-Kyung-Do(瀟湘八景圖), as a text of a cultural landscape, and to clear up the coherence structure between a recognition system and a way of thinking that existed in the cultural phenomenon of Sosang Pal-Kyung. In this study, the symbolism of Pal(八) was summarized and the surface structure and the correlation of each Kyung of Sosang Pal-Kyung was explained in light of semiotics through segmenting and disjointing the lexeme of a landscape while the coherence structure and the meaning of Sosang Pal-Kyung-Ga and Sosang Pal-Kyung-Do as a text were investigated. Sosang Pal-Kyung is based on the view of the Sun and the Moon(or Positive and Negative) and the Eight Trigrams(八卦) for divination and is a linguistic symbol in which human life and the principle of circulation and conversion of nature are expressed as characters and picture texts. Its structure has strong coherence and cohesion, which attempt to move the abstruse truth of nature into human consciousness by developing and corresponding the grammatical structure and form of the sentences and the implicative languages emphasizing the symbolism of the words to the characteristics of similarities and contrast. In addition, Sosang Pal-Kyung expresses human life, the processes of birth and death of nature and the mutual response dialectically by putting various factors of the landscape in the frame of regular formality and structure. It is considered that the image signs in Sosang Pal-Kyung emphasize the theory of circulation of human life and nature are narrative scenery, which one looks at with a contemplative view in the circulation system of the time and the season. The cultural phenomena of Sosang Pal-Kyung in the Joseon Dynasty, which had been handed down from the Goryeo Dynasty, had become the driving force of leading aesthetics of Joseon's art and literature by adding the scenery of the point of view of Sung Confucianism. Its coherence structure was changed, but its cohesion was handed down continuously so that it became not only the basic text of the traditional and cultural landscape but also, the typical Korean-style stereotype of a landscape.

• Cross-Cultural Studies
• /
• v.51
• /
• pp.291-327
• /
• 2018

'Hyesung' and 'Jeilsun' are media that reveal the new searches of the Gaebyeoksa Publishing Company of the 1930s. However, studies in the past did not sufficiently analyze their significance. Furthermore, there are no analyses on how the critical minds of 'Hyesung' and 'Jeilsun' were linked to 'Gaebyeok', which continued publications in 1934. The 1930s when 'Hyesung' and 'Jeilsun' were published, was a time where the media of colonial Chosun was rapidly changing, and it was a time where literary magazines were increasing in quantity. In the 1930s, Gaebyeoksa attempted to actively respond to such changes reflected in the media. This was demonstrated through the publication of the new media 'Hyesung' and 'Jeilsun' and continuing publication of the 'Gaebyeok' magazine in 1935. This study analyzed the literary discourses shown in the magazines published by Gaebyeoksa in the 1930s based on 'Hyesung', 'Jeilsun', and the continued publication of 'Gaebyeok'. Through such analysis, this study examined how the magazines published by Gaebyeoksa perceived the culture and literature of colonial Chosun in the 1930s and in which direction it tried to reorganize this.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.125-148
• /
• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Cross-Cultural Studies
• /
• v.50
• /
• pp.103-130
• /
• 2018

This research aims to explore the associated linguistic features and functions of Chinese as used for business trading purposes, and which is based on a discourse analysis through a case in which a Korean buyer and a Chinese supplier have exchanged Internet based e-mails. The research questions include first, the linguistic functions and characteristics of Chinese shown as identified in this trade case through e-mails, second, the use of Chinese trade specific terms, and third, the apparent and dynamic negotiation strategies that are identified as followed by the cultural value systems which are used for resolving interest conflicts and issues between the buyer and supplier in the course of negotiating business contracts between two parties. The participants of this research pertain to a Korean buyer, James and a Chinese supplier, Sonya. The associated data consists of 74 e-mails exchanged between the two parties, initiated in an effort to begin and complete a trade item, in this case namely the product of napkin holders. The research for the study is based on the discourse analysis and empirically analyses models of Chinese linguistic functions and features. The findings are the following. First, as identified, the specific Chinese functions used and sequenced in this trade case are of a procedure, request, informing, negotiation and persuasion. Second, the essential trade terms used in this business interaction involve the relevant issues of 1) ordering and price negotiating, 2) marking the origin of the products, 3) the arrangement of the product examination and customs declaration for the anticipated import items, 4) preparation of the necessary legal documents, and 5) the package and transport of the product in the final instance. Third, the impact of the similarities and differences in the cultural value systems between Korea and China on the negotiations and conflict resolution during a negotiated contract between two parties are speculated in terms of the use of culturally based techniques such as face-saving and the utilization of uncertainty-avoiding strategies as meant to prevent misunderstandings from developing between the parties. The concluding part of the study discusses the implications for a practical Chinese language education utilizing the linguistic functions and features of the Chinese culture and language strategies as useful in business associations for trading purposes, and the importance of intercultural communication styles based on similar of different identified cultural values as noted between two parties.

• Journal of the Korean earth science society
• /
• v.44 no.6
• /
• pp.655-674
• /
• 2023

This study examined whether the "self-guided interpretation" media in the Yeoncheon area of the Hantangang River UNESCO Geopark are intelligible for visitors. Accordingly, two on-site investigations were conducted in the Hantangang River Global Geopark in September and November 2022. The Yeoncheon area, known for its diverse geological features and the era of geological attraction formation, was selected for analysis. We analyzed the readability levels, graphic characteristics, and alignment with science curriculum of the interpretive media specific to geological sites among a total of 36 self-guided interpretive media in the Yeoncheon area. Results indicated that information boards, primarily offering guidance on geological attractions, were the most prevalent type of interpretive media in the Yeoncheon area. The quantity of text in explanatory media surpassed that of a 12^th-grade science textbook. The average vocabulary grade was similar to that of 11^th- and 12^th-grade science textbooks, with somewhat reduced readability due to a high occurrence of complex sentences. Predominant graphic types included illustrative photographs, aiding comprehension of the geological formation process through multi-structure graphics. Regarding scientific terms used in the interpretive media, 86.3% of the terms were within the "Solid Earth" section of the 2015 revised curriculum, with the majority being at the 4^th-grade level. The 11^th-grade optional curriculum terms comprised the second largest portion, and 13.7% of all science terms were from outside the curriculum. Notably, variations in the scientific terminology's complexity was based on geological attractions. Specifically, the terminology level on the homepage tended to be generally higher than that on information boards. Through these findings, specific factors impeding visitor comprehension of geological attractions in the Yeoncheon area, based on the interpretation medium, were identified. We suggest further research to effect improvements in self-guided interpretation media, fostering geological resource education for general visitors and anticipating advancements in geology education.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.71-88
• /
• 2017

Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.