• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.1
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• pp.33-39
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• 1994

This survey was conducted to investigate the factors affecting on salt accumulation and chemical components of soils cultivated with horticulture crops in plastic film houses. The soil samples were taken from 40 sites in the northern central areas of Korea and were analyzed for the chemical properties and soil separates. The data were evaluated with soil texture and years of cultivation as major factors. The results are summarized as follows : 1. The chemical properties of surface soils in plastic film house were pH 5.80, EC $3.59mScm^{-1}$, O.M. 4.20%, Av. $P_2O_5$ 1,178ppm, $NO_3-N$ 180ppm, Av. $SO_4{^{2-}}$ 353ppm, $Cl^-$ 240ppm, Ex. Na 0.40me/100g. 2. Compared to the outside soil of plastic film house, the inside soil had 2.5~3 times higher contents of $NO_3-N$, Av. $SO_4{^{2-}}$ and $Cl^-$, 1.2~1.8 times higher exchangeable base elements, and 2.8 times higher electrical conductivity. But pH value of the inside soil was lower than the outside soil by 0.3 pH unit. 3. Soil texture classification showed that sandy loam, loam and silt loam were 32.5 %, 37.5 %, and 30.0 %, respectively. The contents of $NO_3-N$, Av. $SO_4{^{2-}}$, $NH_4-N$ and EC value were very high in silt loam soils. Av. $P_2O_5$ content and pH value of sandy loam soils were higher than those of silt loam and loam soils. 4. The contents of O.M. and Av. $P_2O_5$ were higher in long term cultivation, but the contents of $NO_3-N$, Av. $SO_4{^{2-}}$, $Cl^-$, Ex. Mg and Ex. Na including EC of the soil with 2~4 years cultivation were higher than those of the soil with above 5 years cultivation. 5. Multiple linear regression analysis showed that contribution degree of soil chemical properties to the EC was high in the order of $NO_3-N$ > Av. $SO_4{^{2-}}$ > Ex. Na > $Cl^-$ > Av. $P_2O_5$ > $NH_4-N$ > Ex. Mg>Ex. Ca. Among the soil chemical properties the contribution of anions was remarkably high. 6. EC value correlated with ${\sum}A$(total content of anions)as $r=0.932^{**}$ and with ${\sum}C$(total content of cations) as $r=0.452^{**}$.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.3
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• pp.25-34
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• 2020

This study examined the definition and major values, the designated procedures and types, and the designation trend in Korean scenic sites and national parks in the United States. Based on this, the analysis of the characteristics of the designation of the two natural heritages. The results are as follows; First, Scenic Sites has characteristics of complex heritage that includes academic, historical, and humanities values on the basis of landscape. As a natural heritage based on public nature, the U.S. National Park aims to contribute to the people's natural heritage and satisfy both ecological and historical values through the protection of the landscape. Second, the designation of a scenic sites are decided through deliberation by the Cultural Heritage Committee after the request of the owner, manager, or local government or by the authority of the head of the Cultural Heritage Administration. The designated survey is divided into basic resource surveys and resource surveys by type. Since the initial designation of the Sogeumgang Mountain in Cheonghakdong, Myeongju in 1970, the number of designated scenic sites was low until the 2000s, but the number of designated scenic sites has increased rapidly since 2006 due to the policy to promote the scenic site, and the proportion of natural and historical and cultural scenic sites has been balanced. The designation of the U.S. national park is decided by the Congress or the president, and the National Park Service makes a series of decisions on whether to conduct a special resource study of provisional resources through a preliminary inspection survey, whether to satisfy the criteria for designation of national parks based on the results of special resource research, and to prioritize them. The U.S. National Parks have been expanded not only by Congress but also by the president's empowerment to designate them as national monuments. With the integrated operation of the National Park Service, the number of designated cases increased as the national park included the heritage sites under the control of various ministries. In addition, a number of historical areas were designated by the enactment of the Historical Site Act, and recreational areas were designated to provide leisure space and classified and managed in a total of 18 units. Third, the comparison of the designation characteristics of the two heritage properties confirmed that the designation of natural heritage with complex value, the classification of types according to complementary designation system and resource characteristics, the establishment of the competent ministry and the balancing of the heritage according to the designation policy. The two heritages had the characteristics of complex natural heritages that met ecological, historical and academic values at the same time based on landscape and public nature. In addition, both countries have identified a system for deliberating the designation of heritage through a basic resource survey and an in-depth designation survey, and classified each type according to the characteristics of the resource. In addition, the policies for promoting scenic sites in Korea and the integrated operation of the National Park Service in the U.S. influenced the designated aspects of the two heritage sites, balancing natural heritage with historical and cultural heritage. Fourth, the resource types and conservation management methods of Scenic site and National Park were largely related. The natural areas of the U.S. National Park include types of natural monuments in Korea as major resources, and have characteristics similar to natural scenic sites. In addition, historical resources were similar to the criteria for designation of historical and cultural scenic sites in terms of landscape, and the aspects of war and celebrity-related relics were related to the types of historic sites. In terms of conservation management, the natural area of the U.S. national park has a way of keeping the original ecosystem intact, but the Korean natural heritage protection system is likely to be useful for focusing on the resource of viscosity. Meanwhile, historical resources include historical sites and historical and cultural scenic sites in the traditional era, but historical relics in the U.S. National Parks have set a time limit to modern times for war history and celebrity-related relics, and the active provision of entertainment programs based on existing resources was derived as a difference.

• Korean Journal of Breeding Science
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• v.41 no.1
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• pp.16-24
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• 2009

Although leaf characters are important in soybean [Glycin max (L.) Merr.] breeding and development of cultural methods, very little information has been reported. The objectives of this study were to evaluate and analyze the relationships among leaf characters and suggest possible classification criteria for cultivating and wild (Glycin soja Sieb. & Zucc.) soybeans. Total of 94 cultivating and 91 wild soybean accessions from the Soybean Germplasm Laboratory of Chungbuk National University were used for this study. Central leaflet of the second leaf from the top of the plant was selected to measure leaf characters. Average leaf length, leaf width, leaf area, leaf shape index (LSI) of cultivating and wild soybeans were 12.3$\pm$1.25 cm and 6.6$\pm$1.35 cm, 6.8$\pm$1.241 cm and 2.9$\pm$0.92 cm, 55.6$\pm$15.75 $cm^2$ and 14.3$\pm$7.83 $cm^2$, and 1.9$\pm$0.38 and 2.4$\pm$0.53, respectively. Based on LSI, three categories of leaf shape, i.e., oval, ovate and lanceolate, were defined as LIS$\leq$2.0, LSI 2.1~3.0 and 3.1$\leq$LSI, respectively. Percentage of oval, ovate and lanceolate leaf types among cultivating and wild soybean accessions were 78.7%, 17.0% and 4.3 %, and 40%, 15.4% and 4.4%, respectively. Based on leaf length, three categories for cultivating, i.e. short leaf ($\leq$11.0 cm), intermediate (11.1~13.0 cm), and long (13.1 cm$\leq$), and four categories, i.e. short ($\leq$5.0 cm), intermediate (5.1~7.0 cm), long (7.0~9.0 cm), and very long (9.1 cm$\leq$) for wild soybeans were defined. Short, intermediate and long leaf types were about 1/3, 1/2 and 1/6, respectively, in cultivating soybeans, and 15.4%, 40.7% and 39.5%, plus 4.4% of very long leaf type in wild soybean. Cultivating and wild soybeans had leaf thickness, leaf area ratio (LAR), angle and petiol length of 0.25$\pm$0.054 mm and 0.14$\pm$0.032 mm, 40.1$\pm$8.22 and 53.7$\pm$12.02, $37.6{\pm}5.89^{\circ}$ and $54.6{\pm}10.77^{\circ}$, and 23.9$\pm$5.89 cm and 5.9$\pm$2.33 cm, respectively. There were highly significant positive correlations between leaf length and leaf width, and negative correlation between LSI and leaf width both in cultivating and wild soybeans. Although leaf area showed significant correlations with leaf length, leaf width and LIS in cultivating soybeans, wild soybeans showed no significant relationships among these characters. In general, soybeans with oval, ovate and lanceolate leaves were significantly different in leaf width and thickness. Cultivating soybean with oval leaf had greater leaf area, while wild soybeans with oval or ovate leaf had longer petiol than with lanceolate leaf.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.383-391
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• 2007

This study was conducted for an assessment through the estimation of soil loss by each catchment classified by soil catena. Ten catchments, which are Geumgang21, Namgang03, Dongjincheon, Gapyongcheon01, Gyongancheon02, Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02, Youngsangang08, were selected from the hydrologic unit map and the detailed soil digital map (1:25,000) for this study. The catchments like Geumgang21, Namgang03, Dongjincheon, Gapyongcheon01 and Gyongancheon02 were mainly composed with soils originated from gneiss. The catchments like Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02 and Youngsangang08 were mainly composed with soils originated from granites. The grades, which are divided into seven grades with A(very tolerable), B(tolerable), C(moderate), D(low), E(high), F(severe), G(very severe), of soil erosion estimated by USLE in catchments were distributed in most A and B because of paddy land and forestry. In detailed, the soil erosion grade of catchments mainly distributing soils originated from gneiss showed more the distribution of B and C than it of catchments mainly distributing soils originated from granites. The reason of results would be derived from topographic characteristics of soils originated from gneiss located at mountainous. The soil loss according to soil catena linked with Songsan and Jigok series, which are soils originated from gneiss was calculated with $7.66ton\;ha^{-1}\;yr^{-1}$. The soil loss of Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02 which have the soil catena linked with Samgak and Sangju soil series originated from granite, was calculated with $5.55ton\;ha^{-1}\;yr^{-1}$. The soil loss of Youngsangang08 which have the soil catena linked with Songjung and Baeksan soil series originated from granite was calculated with $9.6ton\;ha^{-1}\;yr^{-1}$, but the conclusion on soil loss in this kind of soil catena would be drawn from the analysis of more catchments. In conclusion, the results of this study inform that the classification of soil catena by catchments and estimation of soil loss according to soil catena would be effective for analysis on the grade of non-point pollution by soil erosion in a catchment.

• Korean Journal of Heritage: History & Science
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• v.52 no.2
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• pp.142-171
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• 2019

The dragon is an imaginary animal that appears in the legends and myths of the Orient and the West. While dragons have mostly been portrayed as aggressive and as bad omens in the West, in the Orient, as they symbolize the emperor or have an auspicious meaning, dragons signify a positive meaning. In addition, as the dragon symbolizes the emperor and its type has been diversified considering it as a divine object that controls water, people have tried to express it as a figure. The records related to dragons in the Goryeo dynasty appeared with diverse topics in 'History of Goryeo' and are generally contents related to founding myths, rituals for rain, and Shinii (神異), etc. The founding myth emphasizes the legality of the Goryeo dynasty through the dragon, and this influenced the formation of the dragon's descendants. In addition, the ability to control water, which is a characteristic of the dragon, was symbolized as an earth dragon related to the rainmaking ritual, i.e., wishing for rain during times of drought. Since the dragon was the symbol of the royal family, the use of the dragon by common people was strictly restricted. Furthermore, the association of a bronze dragon mirror with the royal family is hard to be excluded. The type and quantity of bronze double dragon mirrors discovered to have existed during the Goryeo dynasty is great, and the production and the distribution of bronze mirrors with double dragons seem to have been more active compared to other bronze mirrors, as bronze mirrors with double dragons produced during Goryeo and bronze mirrors originating in China were mixed. Therefore, in this article, the characteristics of diverse bronze mirrors from the 10th century to the 14th century in China were examined. It seems that the master craftsmen who produced bronze mirrors with double dragons during the Goryeo dynasty were influenced by Chinese composition patterns when making the mirrors. Because there were many cases where a bronze mirror's country of origin could not easily be determined, in order to identify the differences between bronze double dragon mirrors produced during the Goryeo dynasty and bronze mirrors produced in China, meticulous analysis was required. Thus, to ascertain that Goryeo mirrors were not imitations of bronze mirrors with double dragons originating in China but produced independently, the mirrors were examined using the bronze double dragon mirror type classification system existing in our country. Bronze mirrors with double dragons are classified into three types: Type I, which has the style of the Yao dynasty, includes the greatest proportion; however, despite there being only a small quantity for comparison, Types II and III were selected for the analysis of the bronze mirrors with double dragons made in Goryeo because they have unique composition patterns. As mentioned above, distinguishing bronze mirrors made during Goryeo from bronze mirrors made in China is challenging because Goryeo bronze mirrors were made under the influence of China. Among them, since the manufacturing place of the bronze mirrors with double dragons found at the nine-story stone pagoda in Woljeongsa Temple in Pyeongchang is questionable and the composition pattern of the bronze mirror is hard to find on bronze mirrors with double dragons made in China, the manufacturing place of those bronze mirrors were examined. These bronze mirrors with double dragons were considered as bronze mirrors with double dragons made during the Goryeo dynasty adopting the Yao dynasty style composition pattern as aspects of the composition pattern belonged to Type I, and the detailed combination of patterns is hard to find in mirrors produced in China.

• Korean Journal of Heritage: History & Science
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• v.37
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• pp.65-89
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• 2004

Up to now, the studies for a pond of ancient palace of Korea are mainly achieved in a landscape architectural field. In fact, we can't grasp the general aspects but we are only heard about the fragmentary ruins and remains by the people who are in charge of an archaeological excavation. In this thesis, therefore, I attempt to grasp the relational categories of the ponds of an ancient palace of Korea, and find out the ideological backgrounds of the ponds of a palace construction through classify them excavated so far. The ancient ponds of Korea are divided to the class of square ponds(I) and curved ponds(II) according a shapes of planes. The class of square ponds(I) are subdivided to the form IA of the class of square ponds and form IB of the class of square ponds by whether it has an island, artificial hill and ornamental stone or not. And the class of the curved ponds(II) are divided to the form IIC that is only composed of curves in shore and the form IID that is composed of curves and straight lines. According the size, it is divided to a small size that is below the maximal diameter, 20m, and a large size that is more than 45m, after all, the ponds of the ancient palaces are devided to IAa, IAb, IBa, II Ca, IICb, IIDa. The square ponds and the curved ponds are co-exist from the initial stage when a pond of a place was found in our country and are succeeded or changed after Silla unified the three Kingdoms. In other words, we can infer a continuity from the earlier stage from the fact that there is a flat figure ground mainly constituted by the ponds of a palace mixed up of a straight line and a curved line in United Silla Kingdom while it succeeds the ponds of a palace that has a square form of Goguryo in Balhai. Different from the successional relation of the flat figure grounds, in an aspect of the elements of the construction, the site of the arbor at the top of the island and the bridge facilities in a field of a palace those are not exist in three Kingdoms period are appeared in United Silla Kingdom. The point that this aspect is simultaneously appeared in a neighboring country, or Japan, allows us to infer that there may be some motivations cause the changes in a construction of the ponds of a palace of Korea, China and Japan from the latter half of the 7th century to the first half of the 8th century. The ideological backgrounds of the ponds of a palace construction are divided roughly into Taoism and Buddhism. We can recognize that the ponds of a palace made up of the islands, the artificial hills and the garden rocks reflect Taiosm, considering the records of the ponds a palace of Korea and China are all use the term, Taoism, or the concrete statement represents that the islands, the artificial hills and the garden rocks are used in the description of the ponds of a palace of Korea. Both two are, therefore, obviously differentiated from the ponds of a palace that doesn't include them. We can conclude that the ponds of a palace that doesn't include them are colored by Buddhism since they are overtly distinguished from the class of curved ponds that reflect Taoism at the same period and they are identical with the site of an ancient temples in an aspect of their type and construction.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.