• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.4
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• pp.62-74
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• 2015

This study was carried out to provide examples of planting methods for the construction of street green spaces with abundant greenery by analyzing road type, surrounding land use and planting structures in street green spaces on Port Island, Kobe, Japan. Port Island_(total area: 826ha) is a marine cultural city located in Japan's first artificial island with facilities of urban function and port facilities. The study site was designated at 11 plots of $55{\sim}285m^2$ on Port Island, and topography structure styles were divided into four types with mounding style, slope style, slope and flat style, flat style according to the adjacent roads width. The area adjacent to the middle roads with high levels of noise and pollution set up the mounding style, slope style, slope and flat style of multi-layer structures using topographic properties. The area adjacent to small roads focused on a green strip with shrubs on a flat style. Surrounding land-uses include a public institution, housing complex, and a commercial building. The planting concept was a buffer and landspace function in case of the middle road_(lane 4) while the small road_(lane 2) was a landspace function. Planting species were diverse with Liquidambe formosana, Cinnamomum camphora, Sapium sebiferum, Cedrela sinensis, Laeocarpus sylvestris var. ellipticus, Ginkgo biloba, Prunus serrulata var. spontanea, Zelkova serrata, Quercus glauca, Juniperus chinensis, Magnolia kobus, Rhododendron spp., Camellia japonica, Abelia mosanensis, etc. Planting density was 0.02~0.08(0.04) individual/$m^2$ at the canopy layer, 0.02~0.08(0.04) individual/$m^2$ at the understory layer. Ratio of green coverage was 40.0~173.7(93.0)% at the canopy layer, 2.1~79.8(34.9)% at the understory layer and 17.9~64.2(32.9)% at the shrub layer. $Gr{\ddot{u}}volumenzahl$ was $1.43{\sim}6.67(4.13)m^3/m^2$ at the canopy layer, $0.02{\sim}2.01(0.85)m^3/m^2$ at the understory layer and $0.14{\sim}0.58(0.26)m^3/m^2$ at the shrub layer. The ratio of green coverage of street green space on Port Island was higher than that of Seoul, and particularly, the ratio of green coverage and $gr{\ddot{u}}volumenzahl$ at the shrub layer differed, compared to the main street green space in Korea. The result of this study may be applicable to other coastal reclaimed cities in terms of setting methods for street greenery considering the topography structure, planting structure and planting function.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.16-28
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• 2015

This study is suggested to enlarge the green area and to connect and improve the present green areas by deriving the lines of community greenway using living areas and community spaces close to the life of residence in Nam-gu. The purpose of this paper is to suggest the method of establishing greenway for the formation of community in which the residence can grow the community spirit and love their living space much more. Land-use status, green coverage ratio, and impermeability paving ratio are investigated. The community facilities are classified. The highest is educational facility, which is 7.7%, the green facility is 1.9% and the total area of community facilities which is 21.4%. The total area of Nam-gu is divided into 31 zones in total according to the administrative districts, the mail roads and reserved land of railroad and urban development. The total 20 lines of community greenway lines are chosen and the total length of lines is 18.2km. Finally, the characteristics of community greenway lines are analysed, the characteristics of community greenway lines are overall estimated according to the land-use, the street environment and the community facility. The classification system of community greenway is established on the basis on the function and purpose of greenway, the present status of land-use and the type of community facility. Based on the field investigation, the 6 greenway types are suggested considering the interconnection. The method of establishment of community greenway is suggested according to the principle of function and purpose, the principle of land-use and the principle of use of the facilities. Furthermore, the planting methods suitable to each greenway type are suggested in the building planting case of wall planting, roof planting, veranda planting, etc., and in the complex planting of parks, schools, roads, parking lots and other small areas.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.61-83
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• 2012

A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.174-191
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• 2021

Gangdo (江都), a reproduction of Gaegyeong, was the capital of Goryeo for 39 years. However, due to the urgent wartime situation of the Mongol invasion and the geographical features of Ganghwa Island, the castle system and palace layout were somewhat different from those of Gaegyeong. Gangdo's castle can be understood as a triple castle system consisting of outer castle, middle castle, and inner castle. First, the outer castle was the first to be completed, and it was built at the forefront to prevent the Mongol army from invading in the first place. It is presumed that the section was between Huamdon and Hwadodon in the outer castle during the Joseon Dynasty. The middle castle can be seen as the present 'Middle Castle', a castle built of earth on the outskirts of the Ganghwa-mountain Castle. Considering the sophistication and robustness of the construction method confirmed in the archaeological research, this castle is thought to have been built under a meticulous plan. In other words, as the capital city, it was completed 'at last' as recorded in the Koryo History, after a long 18-year construction process to protect palaces, government offices, and private houses. The inner castle was a castle with the character of a palace. This corresponds to the Old Castle of Ganghwabu (江華府) during the Joseon Dynasty, and it almost coincided with the scale of the composition of Gaegyeong's palace castle. It was a complex functional space, featuring the integration of the palace and the imperial castle, where the main government offices and ancillary facilities, including the palace, were located. Based on the documentary record that these palaces were similar to Gaegyeong's palace, the palace map was overlapped with that of Gaegyeong. The central axis of the building from Seungpyeongmun (昇平門) to Seongyeongjeon (宣慶殿) coincided with Kim Sangyongsunjeol Monument in Ganghwa- Goryeo Palace. Therefore, it seems that the palace of Gangdo had the same basic structure as that of Gaegyeong. However, the inner palace and annexed buildings must have been arranged in consideration of the topographical conditions of Ganghwa, and this is estimated to be the Gunggol area in Gwancheong-ri.

• Korean Journal of Heritage: History & Science
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• v.46 no.1
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• pp.318-345
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• 2013

This study was carried out with a focus on the factor on the periodical space organization of Daebodan (大報壇: the altar of great recompense) in Changdeok Palace, which is significant in terms of political history in the late Chosun Dynasty, and consider the factors in the formation of the structural system through historical records and drawings. Daebodan has the ideology of righteousness to the Ming Dynasty which the hierarchy of the Joseon Dynasty. who felt the crisis of the domination order, imposed as a solution after the Manchu war of 1636. In addition, Daebodan was built by complex factors that entailed the self-esteem of the 'Joseon Centralism Ideology (朝鮮中華)' and the desire of the sacrificial rituals for Heaven that were imminent to the kings of Joseon. Superficially, Daebodan has the spatial organization of the Sajik (社稷) Altar and the placement of an annex building, but had the applied placement due to limited topography and access to the backyard. Furthermore, the lateral structure of Daebodan multiply accepted various factors of the nine step's stairs, the hight of five cheok (尺), the circumstance of two floors that were showed in the altar and platform with small fences and an imperial order including the internal form of Hwangjangbang (黃帳房). Moreover, the name of the alter came from 'the Jiaote Sheng Book of Rites(禮記 郊特牲)' representing 'the suburban sacrifice ritual for Heaven (郊天)', and it was built by not only combining the system of the Sajik Altar in the Joseon Dynasty and China but also avoiding 'excessive etiquette (僭禮).' The point is a remarkable feature shown by the structural system of Daebodan. Thus, it is considered that the 'Notion of Confucian-Cultural Succession (中華繼承意識)' and the desire of the sacrificial rituals for Heaven were expressed by the structure and form of altar. This study examined the process of the creation, expansion, decline and disposal of Daebodan in a chronological order, and found that the ruling ideology of the governing elite by the political and cultural background of the era at each transitional point was reflected in the spatial formation of the altar. On the other hand, as a result of performing a field survey to find the location in accordance with Daebodan in drawing materials, there remains items such as worked stones from Daebodan, precast pavers and fragments of proof tile discovered in the surrounding of tora vine (Actinidia arguta) which is a natural monument of Changdeok Palace. As such, verification through future excavation and investigation is required.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• The Southeast Asian review
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• v.20 no.3
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• pp.263-297
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• 2010

The relics of the Southeast Asian civilizations in the first phase are found with the relics from India, China, and even further West of Persia and Rome. These relics are the historic marks of the ancient interactions of various continents, mainly through the maritime trade. The traces of the indic culture, which appears in the historic age, are represented in the textual records and arts, regarded as the essence of the India itself. The ancient Hindu arts found in various locations of Southeast Asia were thought to be transplanted directly from India. However, Neither did the Gupta Hindu Art of India form the mainstream of the Gupta Art, nor did it play an influential role in the adjacent areas. The Indian culture was transmitted to Southeast Asia rather intermittently than consistently. If we thoroughly compare the early Hindu art of India and that of Southeast Asia, we can find that the latter was influenced by the former, but still sustained Southeast Asian originality. The reason that the earliest Southeast Asian Hindu art is discovered mostly in continental Southeast Asia is resulted from the fact that the earliest networks between India and the region were constructed in this region. Among the images of Hindu gods produced before the 7th century are Shiva, Vishnu, Harihara, and Skanda(the son of Shiva), and Ganesha(the god of wealth). The earliest example of Vishnu was sculpted according to the Kushan style. After that, most of the sculptures came to have robust figures and graceful proportions. There are a small number of images of Ganesha and Skanda. These images strictly follow the iconography of the Indian sculpture. This shows that Southeast Asians chose their own Hindu gods from the Hindu pantheon selectively and devoted their faiths to them. Their basic iconography obediently followed the Indian model, but they tried to transform parts of the images within the Southeast Asian contexts. However, it is very difficult to understand the process of the development of the Hindu faith and its contents in the ancient Southeast Asia. It is because there are very few undamaged Hindu temples left in Southeast Asia. It is also difficult to make sure that the Hindu religion of India, which was based on the complex rituals and the caste system, was transplanted to Southeast Asia, because there were no such strong basis of social structure and religion in the region. "Indianization" is an organized expansion of the Indian culture based on the sense of belonging to an Indian context. This can be defined through the process of transmission and progress of the Hindu or Buddhist religions, legends about purana, and the influx of various epic expression and its development. Such conditions are represented through the Sanskrit language and the art. It is the element of the Indian culture to fabricate an image of god as a devotional object. However, if we look into details of the iconography, style, and religious culture, these can be understood as a "selective reception of foreign religious culture." There were no sophisticated social structure yet to support the Indian culture to continue in Southeast Asia around the 7th century. Whether this phenomena was an "Indianization" or the "influx of elements of Indian culture," it was closely related to the matter of 'localization.' The regional character of each local region in Southeast Asia is partially shown after the 8th century. However it is not clear whether this culture was settled in each region as its dominant culture. The localization of the Indian culture in Southeast Asia which acted as a network connecting ports or cities was a part of the process of localization of Indian culture in pan-Southeast Asian region, and the process of the building of the basis for establishing an identity for each Southeast Asian region.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.168-184
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• 2022

This paper examined the construction techniques of the earthen fortifications in the Hanseong Period of Baekje Kingdom, which has been researched most frequently among the Three Kingdoms. The construction processes of the Earthen Fortifications were reviewed and dividing into 'selection of location and construction of the base', 'construction of the wall', and 'finish, extension and repair'. The results show that various techniques were mobilized for building these earthen fortifications. Techniques which were adequate for the topography were utilized for reinforcing the base, and several other techniques were used for constructing the wall. In particular, techniques for wall construction may be clearly divided into those of the fill(盛土) and panchuk(版築) techniques. The fill method has been assumed since the 2000s to have been more efficient than the panchuk technique. This method never uses the structure of the panchuk technique and is characterized by a complex soil layer line, an alternate fill, use of 'earth mound(土堤)'/'clay clod(土塊)', and junctions of oval fill units. The fill method allows us to understand active technological sharing and application among the embankment structures in the period of the Three Kingdoms. The panchuk technique is used to construct a wall using a stamped earthen structure. This technique is divided into types B1 and B2 according to the height, scale, and extension method of the structure. Type B1 precedes B2, which was introduced in the late Hanseong Period. Staring with the Pungnap Earthen Fortification in Seoul, the panchuk technique seems to have spread throughout South Korea. The techniques of the fill and panchuk techniques coexisted at the time when they appeared, but panchuk earthen fortifications gradually dominated. Both techniques have completely different methods for the soil layers, and they have opposite orders of construction. Accordingly, it is assumed that both have different technical systems. The construction techniques of the earthen fortifications began from the Hanseong Period of Baekje Kingdom and were handed down and developed until the Woongjin-Sabi Periods. In the process, it seems that there existed active interactions with other nations. Recently, since studies of the earthen fortifications have been increasing mainly in the southern areas, it is expected that comparative analysis with neighboring countries will be done intensively.