• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

• Management & Information Systems Review
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• v.39 no.2
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• pp.181-193
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• 2020

This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.615-627
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• 2012

The market penetration of the smart phones has brought significant changes to the related industries. As the mobile phone market as well as the smart phone application market are growing rapidly, competition among small-size application developers has become severe. However, due to the severe competition and expensive market entry costs, the developers argue that it is necessary to develope the applications from the perspective of the users. However, studies on application development from the users' perspectives are still in the early stages and they have not provided various approaches. Therefore, based on the Open Coding method of Ground Theory, this study collected data on applications review from related communities and blogs of Korean web portal sites, and identified indices which users consider important when they use the applications. In addition, we conduct a comparative analysis between those indices by calculating their frequency of exposure. As a result, a total of 30 sub-categories of indicators such as amusement, controllability, versatility and ease of use appeared to be predominant to users and those lower categories were grouped into five categories; sensibility, design, technology, price, and social skills. The results of this study suggest to the application developers the guidelines of user oriented design and development. It can be used to develop the evaluation tool for application usability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.417-428
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• 2020

Housekeeping genes are expressed in cells of all organisms and perform basic cellular functions such as energy generation, substance synthesis, cell death, and cell defense. Accordingly, the expression levels of housekeeping genes are relatively constant, and thus they are used as reference genes in gene expression studies, such as protein expression and mRNA expression analysis of target genes. However, the levels of expression of these genes may be different among various tissues or cells and may change under certain circumstances. Therefore, it is important to select the best reference gene for specific gene expression research by exploring the stability of housekeeping gene expression. This review summarizes housekeeping genes found in humans, chickens, pigs, and rats in the literature and estimates expression stability using geNorm, NormFinder, and BestKeeper software. The most suitable reference housekeeping gene can selected based on expression stability according to the experimental conditions of the gene expression study and can thus be applied to data normalization.

• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1433-1442
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• 2018

This study develops and improves the EZ Touch App of the scorecard application (app) using the smartphone and the pad, and works with the customer management system (C/S). The research was conducted as follows. First, how do you handle the EZ Touch input method on a scorecard? Second, how to configure the platform of customer (member) management system (C/S) and data server system? Third, does EZ Touch App work organically with customer management system (C/S)? The developed EZ Touch is entered into the scorecard as an input method using the gesture as a result of this research, and it is linked with the C/S system to organize the review function, hall information function, field coaching function through score, It can be used for applications such as information management functions and statistics through differentiated statistics. However, there are some problems and improvements in user convenience in real time use. I think there is a need to study to solve this problem in the future. EZ Touch input method is input to the scorecard by inputting gesture of the finger as a result of this study, and it is linked with this, and it is possible to use differentiated statistics such as review function, hall information function, field coaching function, It is the purpose of the study to improve the technical competitiveness of the product by developing the application.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1327-1334
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• 2015

Cancer pain is a very important factor in cancer patients refractory to drop the quality of life of cancer patients. The worldwide trend is an integrated effort by both the western medicine and korean traditional medicine of treatment increases to reduce cancer pain. There are many studies related to cancer pain through an integrated medicine approach. Many study was reported that acupuncture treatment is effective for fatigue, xerostomia, insomnia, anxiety and quality of life. However, despite the practical clinical effects and various case reports of acupuncture, many still disagree about the significance of an integrated treatment of pain reduction with acupuncture. Therefore, we has identified that reduce effect of comprehensive and integrative treatment using acupuncture for cancer pain through publication review. And we evaluated effect of comprehensive and integrative treatment using acupuncture through summary of values in each publication.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7485-7493
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• 2015

With the popularity of Korean Wave, making cultural goods specific for Hallyu tourists is getting more important. However, there are mainly daily life goods using celebrity character-based ones. Remarkably, there are only a few cultural goods especially in practicality-based clothing category. In particular, few cultural goods related to children's wear have been developed. Therefore, if children's wear is developed as Korean Wave cultural goods considering Chinese consumers' pattern and Korean Wave cultural goods, it will be helpful for revitalizing the Korean Wave and Korea's fashion market. In this regard, the purpose of this study is to develop children's wear design as Korean Wave cultural goods, thereby presenting empirical research results and fulfilling its following objectives: First, it is to identify the concept of Korean Wave cultural goods, to analyze the current status to finally establish data to develop Korean Wave cultural goods needed at this time. Second, it is to make real-life size works through development of designs to provide the empirical data for Korean Wave cultural goods market. For the research method and contents the review of the previous research, in-depth interview for qualitative research, and empirical research using market research and development of work were performed. Through the final research outcomes, Korean Wave cultural goods, the children's wear that can meet the consumer's needs were presented as empirical data. The study can be used as basic data for domestic fashion market and cultural product market and it is meaningful as a reference for the analysis on the Chinese consumers' needs.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.149-157
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• 2010

As the use of the Internet has recently increased, the demand for opinion information posted on the Internet has grown. However, such resources only exist on the website. People who want to search for information on the Internet find it inconvenient to visit each website. This paper focuses on the opinion information extraction and analysis system through Web mining that is based on statistics collected from Web contents. That is, users' opinion information which is scattered across several websites can be automatically analyzed and extracted. The system provides the opinion information search service that enables users to search for real-time positive and negative opinions and check their statistics. Also, users can do real-time search and monitoring about other opinion information by putting keywords in the system. Proposed technologies proved to have outstanding capabilities in comparison to existing ones through tests. The capabilities to extract positive and negative opinion information were assessed. Specifically, test movie review sentence testing data was tested and its results were analyzed.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Korean Journal of Environmental Agriculture
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• v.40 no.3
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• pp.219-230
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• 2021

BACKGROUND: Biochar is a solid material converted from agricultural biomass such as crop residues and pruning branch through pyrolysis under limited oxygen supply. Biochar consists of non-degradable carbon (C) double bonds and aromatic ring that are not readily broken down by microbial degradation in the soils. Due to the recalcitrancy of C in biochar, biochar application to the soils is of help in enhancing soil carbon sequestration in arable lands that might be a strategy of agricultural sector to mitigate climate change. METHODS AND RESULTS: Data were collected from studies on the effect of biochar application on soil C content conducted in East Asian countries including China, Japan and Korea under different experimental conditions (incubation, column, pot, and field). The magnitude of soil C storage was positively correlated (p < 0.001) with biochar application rate under field conditions, reflecting accumulation of recalcitrant black C in the biochar. However, The changes in soil C contents per C input from biochar (% per t/ha) were 6.80 in field condition, and 12.58 in laboratory condition. The magnitude of increment of soil C was lower in field than in laboratory conditions due to potential loss of C through weathering of biochar under field conditions. Biochar production condition also affected soil C increment; more C increment was found with biochar produced at a high temperature (over 450℃). CONCLUSION: This review suggests that biochar application is a potential measures of C sequestration in agricultural soils. However, as the increment of soil C biochar was affected by biochar types, further studies are necessary to find better biochar types for enhanced soil C storage.