• Journal of Practical Agriculture & Fisheries Research
• /
• v.21 no.2
• /
• pp.103-114
• /
• 2019

In this study we examined the preferences of college life factors for students at Korea National College of Agriculture and Fisheries(KNCAF). Analytical techniques of unstructured data used opinion mining and text mining techniques, and the results of text mining were visualized as word cloud. And those results were used for statistical analysis of the students' willingness to farm after graduation. The items of the favorable survey consisted of 10 items in 5 areas including university image, self-capacity, dormitory, education system, and future vision. After classifying the emotions of positive and negative in the collected questionnaire, a dictionary of positive and negative was created to evaluate the preference. The items of 'college image' at the time of university support, 'self after 10 years' after graduation, 'self-capacity' and 'present KNCAF' showed high positive emotion. On the other hand, positive emotion was low in the items of 'college dormitory', 'educational course', 'long-term field practice' and 'future of Korean agriculture'. In the cross-analysis of the difference in the will to farming according to gender, farming base, and entrance motivation, the will to farm according to gender and entrance motivation showed statistically significant results, but it was not significant in farming base. Also in binary logistic regression analysis on the will to farming, the statistically significant variable was found to be 'motivation for admission'

• Information Systems Review
• /
• v.21 no.4
• /
• pp.175-195
• /
• 2019

This study conducted both big data and netnography analysis to analyze consumer needs and behaviors of online consumer community. Big data analysis is easy to identify correlations, but causality is difficult to identify. To overcome this limitation, we used netnography analysis together. The netnography methodology is excellent for context grasping. However, there is a limit in that it is time and costly to analyze a large amount of data accumulated for a long time. Therefore, in this study, we searched for patterns of overall data through big data analysis and discovered outliers that require netnography analysis, and then performed netnography analysis only before and after outliers. As a result of analysis, the cause of the phenomenon shown through big data analysis could be explained through netnography analysis. In addition, it was able to identify the internal structural changes of the community, which are not easily revealed by big data analysis. Therefore, this study was able to effectively explain much of online consumer behavior that was difficult to understand as well as contextual semantics from the unstructured data missed by big data. The big data-netnography integrated model proposed in this study can be used as a good tool to discover new consumer needs in the online environment.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.11
• /
• pp.521-526
• /
• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.

• Women's Health Nursing
• /
• v.6 no.2
• /
• pp.203-217
• /
• 2000

The purpose of this study was done to explore the pregnant women's decision-making process about their infants feeding method. Data collection involved the in-depth unstructured interviews with 12 participants from January 1998 to January 1999. Data analysis was done by the grounded theory method. The 112 concepts, 29 sub-categories were confirmed in the analysis. The sub-categories were again grouped into 14 categories: expectation, situational condition, inevitability of breast-feeding, social recognition, self-awareness as mother, harmony, consideration, pursuit of ease, effect of external environments, lack of knowledge, hardening, the best choice, control, and bargain. " Adjustment through recognizing of motherhood" was the key category that was related to all categories. "Adjustment through recognizing of motherhood" was a process in which the mother became aware of mothering and sharing, and in which she considered herself or infant's needs and their priorities. This research will help nurse to understand mother's needs better. Therefore, nurse will be able to assist mother making the best decision for herself and her infant.

• Women's Health Nursing
• /
• v.14 no.1
• /
• pp.44-55
• /
• 2008

Purpose: This study was done to assess the personal experiences of the coping process during pregnancy for single mothers. Methods: The participants were 17 single mothers who had stayed in a social welfare facility. Data was collected with an in-depth unstructured interview. Data analysis was done by the grounded theory method. Results: One-hundred twelve concepts and 49 sub-categories were confirmed in the analysis. The sub-categories were grouped into 19 categories; escape from a miserable family, wrong meeting, openness of sex, defenseless state of pregnancy, inevitable result of pregnancy, heartbreak by herself, closure, isolation, difficult situation of being alone, stigma, supporting & protecting, helplessness, seeking, empowering, feeling of loss, conflict, facing issues, assuring a fresh start and becoming-mature. "Being driven over the edge of a cliff" was the key phenomenon which the single mothers experienced during the process of pregnancy. Conclusion: The above results will help nurses assessing single pregnancy mothers' needs and developing a nursing intervention program for supporting them. Therefore, nurses will be able to stop them from "being driven over the edge of cliff". A more vigorous nursing intervention is suggested for the research of the vulnerable classes of medical health care including single pregnant mothers.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.3
• /
• pp.154-161
• /
• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.17 no.2
• /
• pp.149-158
• /
• 2010

Purpose: This study was done to gain understanding of what career and related experience mean to individuals undergoing hemodialysis. Methods: Ten male patients receiving hemodialysis participated in the study. Data collection took place between November 18, 2008 and February 10, 2010, via unstructured interviews. Data collection and analysis were conducted simultaneously, and Colaizzi's phenomenological method (1978) was used for the analysis. Results: The significance the participants found in their "dual" life as worker and dialysis patients was classified into five categories: 'Recognition of self-existence value', 'My health comes before my work', 'Being afraid of stigma', 'Limitation of restricted work', and 'Difficulty with time management.' Conclusion: It was found that the dialysis patients showed ambivalent feelings towards their careers, hoping they will be able to continue to work yet fearing that the continued work might break balance the between their livelihood and healing. Therefore, it is recommended that hours for hemodialysis be more flexible to ensure that patients can keep their jobs and better manage their time while undergoing treatment.

• International journal of advanced smart convergence
• /
• v.9 no.4
• /
• pp.198-202
• /
• 2020

User review sites are spaces where users can freely post and share their opinions, which are trusted by many people and directly influence sales. In addition, they overcome the limitations arising from existing requirements collection and are able to gather the needs of large numbers of different people at a low cost. Therefore, such sites are attracting attention as new spaces for understanding user needs. In a previous study, a user review analysis was attempted using 5W and 1H, and we inferred that a sentence containing "when" has special information based on the user experience. In addition, the requirements of the derivative activities in a user review can identify more user needs than the general requirements of derivative activities. In this paper, we propose a systematic method of deriving "when" sentences contain meaningful information from user reviews and converting them into use cases, which is one of the requirements of a specification method. This method converts unstructured data into structured data such that it can be included as the user requirements during software development from user comments expressed in natural language. This method will reduce project failures and increase the likelihood of success by enabling an efficient collection and analysis of user needs from valuable user reviews.

• Journal of Digital Contents Society
• /
• v.15 no.4
• /
• pp.533-545
• /
• 2014

According to the evolving of IT technologies, the amount of data we are facing increasing exponentially. Thus, the technique for managing and analyzing these vast data that has emerged is a distributed processing system of big data. A quality evaluation for the existing distributed processing systems has been proceeded by the structured data environment. Thus, if we apply this to the evaluation of distributed processing systems of big data which has to focus on the analysis of the unstructured data, a precise quality assessment cannot be made. Therefore, a study of the quality evaluation model for the distributed processing systems is needed, which considers the environment of the analysis of big data. In this paper, we propose a new quality evaluation model by deriving the quality evaluation elements based on the ISO/IEC9126 which is the international standard on software quality, and defining metrics for validating the elements.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.46 no.5
• /
• pp.772-788
• /
• 2022

This study investigates whether the image of the casual Hanbok brand is being communicated to consumers successfully. We conducted a semantic network analysis to identify ways of revitalizing communication between casual Hanbok brands and consumers; in addition, we quantitatively evaluated the effectiveness of communication marketing through Quadratic Assignment Procedure (QAP) analysis. Unstructured data from 2014-2021 were collected through portal sites and then refined and networked. Our analysis showed that casual Hanbok brands generally target younger people and that different brands employ similar methods to promote and popularize the casual Hanbok style. Consumers tended to recognize and show interest in casual Hanbok, suggesting the potential to expand the market to Blue Ocean. However, some of our findings revealed the potential factors of style coordination risk and prejudice against existing Hanbok, which could potentially hinder casual Hanbok's uptake and adoption. We conclude that increasing the demand for casual Hanbok depends not only on delivering an accurate brand image to consumers but also on balancing fashion with traditional images when planning products and providing styling information.