• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.171-176
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• 2022

This paper examines the historical meaning and value of sound art curating as a key type of interdisciplinary and convergence art practice that has been unfolding since the mid-20th century. Accordingly, this paper summarizes the developmental process from the beginning of 'sound art' to the present, but examines the context of visual art in which the material 'sound' functioned in chronological order, and focuses on curating cases of major sound art exhibitions. The purpose of this study is to analyze the impact and contemporary significance of the provided aesthetic experience. To this end, the text is divided into three sections and developed. The first section recognizes that the late 19th century futurist and Dadaist sound poetry, followed by Marcel Duchamp's 1913 attempt to combine musical score with visual art, had a profound influence on the visual music of avant-garde composer John Cage. This explains why this background caused the emergence of exhibitions dealing with 'sound' as a new medium. The second section explains that in the 1970s, sound as an artistic medium played a role in reflecting the critical relationship with the exhibition space dominated by visuality. In the third section, we analyze the curatorial methodology that allows the audience to experience sound as if it were a visual object within the organization of the exhibition hall from the 1980s to the present. Through this process, this paper critically treats the historical practice of customizing the perceptual structure in the exhibition hall, and considers the meaningful methodology of sound art curating considering the role of sound full of vitality in the contemporary art scene.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.3 no.1
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• pp.10-19
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• 2000

Due to the urbanization, concentrated population, and limited land exploitation in the modern society, the environment surrounding that we live in is getting polluted more and more, and it has become hard even to let urban children experience the nature. This research was conducted to help people recognize the importance of our natural resources through the environmental education of elementary school and to use school's practical open-space for the Indigenous Plants education. The results of this study are as follows : First, the status of a plant utilization in our institutional education : There were 362 species totally of 124 species of Trees, 156 species of Herbs, 63 species of Crops, and 19 species of Hydrophytes which appear in the elementary school text book. Of all, the most frequently appearing species of tree were the Malus pumila var. dulcissima, Pinus densijlora, Citrus unshiu, Diospyros kaki. Second, the effect of plant education using the land around schools : The result of research on the open-space of the 19 elementary schools located in Mapo-gu showed that most of the species planted are the Juniperus chinensisrose, Hibiscus syriacus. Pelargonium inquinans in the order of size, and the plants appearing in text book were grown in the botanical garden organized in 7 schools. Especially most of the Indigenous Plants were being planted in botanical garden, and Pinus densijlora, Abeliophyllum distichum, Polygonatum var. plurijlorum, Liriope platyphylla and so on. Last, the result of this research on recognition of Environment, Planting education and Indigenous plants : It showed that educational necessity of students and teachers about environment and Indigenous Plants was more than 80%. The management of botanical garden was conducted by some teachers and managers. The results of this study suggested that we needed the reconstruction of curriculum, the efficient application of plant education for effectiveness of using school environment and monitoring continually and construction information sources for the better environment education in the elementary schools.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.749-758
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• 2004

In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Archives of design research
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• v.19 no.1 s.63
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• pp.201-214
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• 2006

Modern society is an age of vagueness and confusion. In addition, vagueness, complexity and variety are seen throughout art including modern philosophy, literature, and environmental design. A phenomenon like this shows that modern society has integrated different components as an organic relationship frequently crossing the boundary of fields. This feature can be regarded as hybrid related with accepting contradictory components and binding them into one under relationship between part and whole. As new design concept, presented are attitude to accept the two instead of attitude to select one of the alternatives, abundance instead of dearness, and ambiguity instead of simplicity. This principle has a crucial influence on creative design providing opposing contradiction and several alternative plans as non-deterministic form not completed one and, above all, useful information in mutual dependence and mutual relationship. When it comes to hybrid, therefore, a strategy is needed to consider layer of several fields getting out of standardizing space into a single space. As an event of this situation and concept, space experience means behaving freely based on experience of users' body. It can be known that this experience brings about users' more dynamic experience in comparison with the experience of seeing environmental design from a viewpoint of visual ism on the existing simplicity. Such a practical experience is subjective, synesthetic, and non-observational one. Therefore, hybrid has brought active users to the stage, which is distinguished from synesthesia felt through body's experience, not through observational attitude and visual space which achieve former balance and harmony with non-determination. That's because hybrid creatures are turning to a product resulted from creative imagination instead of from reappearance which makes text visualized. Such experience performed by user's active participation collapses the boundary between special elite-centered art and daily life and it is the present progressive form showing creation process of future events and new esthetic experience.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.3
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• pp.48-57
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• 2018

In this study, we conducted an analysis on the actual field materials and the ancient text of January 2017. First, Yuyin ShanFang is one of the famous garden in the Lingnan Region, and its total area is $1598m^2$. Wobin called the name 'Yuyin(餘蔭)' meaning the virtues of his ancestors. Second, if we analyze the poem written by Wobin, we can classify it as a phrase expressing the world beyond the future, a poem expressing the ideas of family and romantic ideas. Third, the space spread to the south around the shrine building in the middle of the site was largely a residential space, according to the analysis of the site's layout and spatial composition. Fourth, the spatial component of the hydronic acid is analyzed. The pavilion area is the Hanchwi-Pavilion, which is designated in the Wongrim, and Gyesang-Pavilion, which is a unique range that describes the peak of the garden. Fifth, Yuyin ShanFang has five ponds that are very diverse in shape. It is characteristic of us to stand on a technical boundary. Sixth, Seokgasan was referred to as Gyeongbansan, which was named after The builder Wobin and his descendants who passed it. Seventh, Hwachang is characterized by a wooden bull window and a compound glass. Eighth, the alumni style is not as diverse as the alumni style of the Suzhou traditional garden, but it features various forms and colorful pictures on the front of the alumni. Ninth, the one-piece sculptures of the interior of a building are expressed themes such as Gilsang, Sukjeong, Daoism, Palseom, and others. Finally, Trees planted in Yuyin ShanFang are mostly tropical plants, and some of them have symbolic meaning. Because the weather here is good for growing fruit, so planted a lot of fruit trees.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.2
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• pp.36-48
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• 2015

This study aims to contemplated the enjoying culture of Gyeonghwasejok's garden in late Joseon dynasty. It was track down the behavior from cultural perspective by using recorded in literature. The results were as follows. First, Gyeonghwasejok was the main principal of the garden at Hanyang in Joseon Dynasty. There are established residence in the downtown and make a garden. Garden organizer recognized to fine conditions of residences even crowded downtown. As a result people tried to include habitation and garden culture for preserve their cultural benefit. Secondly, Seongsisanrim culture has appeared of common in site selection of garden for occupies the scenic beauty. Garden was surrounded by scenic beauty. Garden organizer was formed archival culture for owning the beautiful landscape through creation of guguk(九曲), designation of space and lettering on rocks. Thirdly, Formation of the collection culture was placed of various ornaments inside garden. A behaviour of landscape view and ornaments appreciation led to the archival culture such as Won-rim-gi(園林記) and essay(小品文). Moreover, hold a friendship meeting for sharing garden culture. Fourthly, Attention of flowering plants was extended to development of gardening hobby such as fashion of pot-planting, planted to exotic tree. It was know that the plants are recognized as favorite elements by target of appreciation according to introduction of plants inside garden. In addition, facility of horticulture and kitchen garden were placed inside garden. Fifth, Influx of chinese garden culture influenced construction of garden space in late Joseon dynasty. Garden organizer recognizes garden as a ideal space by garden aesthetics that Hojungcheonji(壺中天地). And the imitation of Chinese garden culture such as collecting of Chinese's ornaments has become a high-level culture.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.1-31
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• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.