• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of Nutrition and Health
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• v.48 no.1
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• pp.113-121
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• 2015

Purpose: The purpose of this study was to investigate satisfaction with and perception of the school meal service according to middle school students and dieticians/dietetic teachers in Gwangju area who experienced change to the free meal service and the main contents were as follows. Methods: The research subjects were 197 students (99 boys and 98 girls) and 42 dieticians/dietetic teachers were recruited. Results: Compared to the free meal service before, satisfaction of students was high (53.8%), and 69.9% of students said there was no change in the school meals, however a significant difference was observed between gender. Overall 80.2% of middle school students said that there was no change in menu, 70.6% were no change in the frequency of food with high preference, and 64.0% were no change in leftover of meals. 85.7% of dieticians/dietetic teachers said that there was no change in the student's satisfaction according to the conversion of free meal services; 59.5% of dieticians/dietetic teachers said that there was no change in the frequency of foods with high preference, the variety of vegetables was increased in the qualitative change item of food materials, and 95% of them were not aware of change in the amount of students' leftover foods. Dieticians/dietetic teachers had limitations in selecting menus with purchase and costs of food materials (26.2%) by conversion of the free meal service and their priority considered was the food cost (45.2%) when they selected menus. Change in feeding affairs was office work management (26.2%) and recipe research and development (19.0%). Conclusion: With the results of this study, the satisfaction with the school meal service was not changed in the awareness of students and dieticians/dietetic teachers. Therefore further study is needed to determine the middle school's satisfaction with school meals based on a variety of factors including the environmental food meal services.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.12
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• pp.1873-1880
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• 2015

The purpose of this study was to survey intention to purchase home meal replacement (HMR) made with eco-friendly food ingredients as well as need for development while analyzing importance and performance of HMR made with eco-friendly ingredients for its commercialization. From September 2014 to March 2015, questionnaires were filled out by respondents. Of the 422 questionnaires that were returned, 412 were used with 10 discarded as incomplete. Regarding reasons behind purchasing HMR, the highest percentages of both males and females answered 'ready to eat'. Almost all respondents spent 'less than 10,000 won' each time they purchased HMR. Regarding place they bought HMR, a higher percentage of respondents answered 'convenience store' and 'discount retail chain store'. In terms of improvements needed for HMR, the highest percentage of males answered 'development of a variety of menus' while the highest percentage of females answered 'change in food ingredients' at 37.7%. For development of HMR made with eco-friendly ingredients, most respondents replied that there is a need for development. Regarding intention for purchasing HMR made with eco-friendly ingredients, 66.7% of males and 73.5% of females answered they have intention to buy. Important performance analysis showed a need to improve performance of 'safety of food ingredients', which was located close to the second quadrant. To improve performance for 'safety of food ingredients', safety must be ensured through use of eco-friendly ingredients, and a systematic process for managing hazardous materials that could arise during the manufacturing process has to be developed.

• Journal of Nutrition and Health
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• v.44 no.1
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• pp.61-73
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• 2011

The aim of this study was to develop a reliable dietary questionnaire to assess human exposure to food-borne hazards. Eleven food-borne hazards were chosen as a priority control list through a literature review and advisory committees. The 11 food-borne hazards were phthalate, aflatoxin, bisphenol A, polycyclic aromatic hydrocarbons, dioxin, polychlorinated biphenyls, mercury, lead, cadmium, arsenic, and acrylamide. The characteristics, exposure level, and paths of these hazards were reviewed, and questionnaire items were identified to assess human exposure from the literature. A questionnaire was developed for each selected food based on its characteristics. Based on the items in the individual questionnaires, a comprehensive questionnaire, which contained demographic characteristics, job information, socioeconomic factors, health related lifestyles, and dietary behaviors, was developed. A 99-item food frequency questionnaire (FFQ) to assess food-borne hazard exposure was also developed. The FFQ included frequency of food intake during the previous year, container type for purchasing and storing food, and cooking method. The questionnaire developed in this study could be applied to assess dietary factors during an exposure assessment of food-borne hazards in a large population. A validation study for the questionnaire is needed before applying it to surveys.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.4
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• pp.33-49
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• 2019

The purpose of this study was to investigate the changes in the experiences of visitors of Yeonnam-dong during the period covering the development of a linear park, the Gyeongui Line Park. This study used a text mining technique to analyze Naver Blog postings of those who visited Yeonnam-dong from June 2013 to May 2017, divided into four periods -from June 2013 to May 2014, from June 2014 to May 2015, from June 2015 to May 2016 and from June 2016 to May 2017. The keywords used were 'Yeonnam-dong', 'Gyeongui Line' and 'Yeontral Park' and the data was further refined and resampled. A semantic network analysis was conducted on the basis of the co-occurrences of words. The results of the study were as follows. During the entire period, the main experience of visitors to Yeonnam-dong was 'food culture' consistently, but the activities related to 'market', 'browsing', and 'buy' increased. Also, activities such as 'walk', 'play' and 'rest' in the park newly appeared after the construction of the park. Moreover, more diverse opinions about the Yeonnam-dong were expressed on the blog, and Yeonnam-dong began to be recognized as a place where a variety of activities can be enjoyed. Lastly, when the visitors wrote about the theme 'food culture', the scope of the keywords expanded from simple ones, such as 'eat', 'photograph' and 'chatting' to 'market', 'browsing', and 'walk'. The sub-themes that appeared with the park also expanded to various topics with the emergence of the Gyeongui Line Book Street. This study analyzed the change of experiences of visitors objectively with text mining, a quantitative methodology. Due to the nature of text mining, however, the subjective opinions inevitably have been involved in the process of refining. Also, further research is required to assess the direct relationship between these changes and park construction.

• Land and Housing Review
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• v.13 no.4
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• pp.55-71
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• 2022

Recently, the domestic department store industry is growing into a complex shopping cultural space, which is advanced and differentiated by changes in consumption patterns. In addition, competition is intensifying across 70 places operated by five large companies. This study investigates the determinants of the visits to department stores using the big data concept's automatic vehicle access system (pos) and proposes how to strengthen the competitiveness of the department store industry. We use a negative binomial regression test to predict the frequency of visits to 67 branches, except for three branches whose annual sales were incomplete due to the new opening in 2021. The results show that the demand for visiting department stores is positively associated with airport, terminal, and train stations, land areas, parking lots, VIP lounge numbers, luxury store ratio, F&B store numbers, non-commercial areas, and hotels. We suggest four strategies to enhance the competitiveness of domestic department stores. First, department store consumers have a high preference for luxury brands. Therefore, department stores need to form their own overseas buyer teams to discover and attract new luxury brands and attract customers who have a high demand for luxury brands. In addition, to attract consumers with high purchasing power and loyalty, it is necessary to provide more differentiated products and services for VIP customers than before. Second, it is desirable to focus on transportation hub areas such as train stations, airports, and terminals in Gyeonggi and Incheon. Third, department stores should attract tenants who can satisfy customers, given that key tenants are an important component of advanced shopping centers for department stores. Finally, the department store, a top-end shopping center, should be developed as a space with differentiated shopping, culture, dining out, and leisure services, such as "The Hyundai", which opened in 2021, to ensure future growth potential.