• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.359-372
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• 2022

This study aimed to derive a YouTube content strategy that can be exposed to Trending for a long time by comparing the features of 20 channels in the short/long term using 'YouTube Trending' data in 2021. First, through Pearson's correlation analysis, we found that various factors such as 'the number of title or tag letters' related to long-term exposure, and set this as an index to compare features. As a result, 1)'video title' of about 40-45 letters without excessive special characters, 2)'video length' within 10 minutes, 3)'Video description' is effective when writing 2-3 sentences and adding SNS information or including 3 key tags. Also, it would be more effective if you set key tag pairs such as (먹방, mukbang), (역대급, 레전드) derived through text mining. Through this, the channel will spread globally, bringing various advantages, and will be used as an indicator to evaluate the globality of the channel.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Acupuncture Research
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• v.21 no.3
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• pp.265-282
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• 2004

Objective : The aim of this study was to review systemically clinical trials on the effectiveness and safety of herbal medicines in the treatment of osteoarthritis. Methods : Computerized literature searches were carried out on seven electronic databases, and hand-searching on some chinese medical journals in library of Kyung Hee Medical Center. Trial data were extracted in a standardized, predefined manner and assessed independently. Results : 1. Thirty reports of clinical trials and two reports of meta-analyses concerning herbal medicine were collected and reviewed. Among these reports three medical herbs were applied as topical medicine and others as internal medicine. 2. The western studies established NSAIDs or placebo as their control group. Five chinese reports established formulated herb pill(Ruanshnagshenjin pill) as their control group and Six did not establish a control group at all. 3. ACR was the most highly used diagnostic criteria in the western studies while the Chinese used their official criteria established by their government or the criteria of their text books. 4. 20 reports chose the Lequesne functional index, SHAQ, WOMAC OA index, AIMS, and their own unique scoring system as the criteria of analysing the effect. Others chose clinical symptoms, articular functions, and lab finding as their criteria. 5. 7 single herbs and 19 formulated herbs were studied. Among the formulated herbs, Achyranthes japonica was studied in 10 of the studies and Angelica gigantis Radix in 8, making them the most often studied herbs among the studies.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3874-3884
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• 2000

An information retrieval system has to retrieve all and only documents which are relevant to a user query, even if index terms and query terms are not matched exactly. However, term mismatches between index terms and qucry terms have been a serious obstacle to the enhancement of retrieval performance. In this paper, we discuss automatic term normalization between words in text corpora and their application to a Korean information retrieval system. We perform two types of term normalizations to alleviate semantic term mismatches: equivalence class and co-occurrence cluster. First, transliterations, spelling errors, and synonyms are normalized into equivalence classes bv using contextual similarity. Second, context-based terms are normalized by using a combination of mutual information and word context to establish word similarities. Next, unsupervised clustering is done by using K-means algorithm and co-occurrence clusters are identified. In this paper, these normalized term products are used in the query expansion to alleviate semantic tem1 mismatches. In other words, we utilize two kinds of tcrm normalizations, equivalence class and co-occurrence cluster, to expand user's queries with new tcrms, in an attempt to make user's queries more comprehensive (adding transliterations) or more specific (adding spc'Cializationsl. For query expansion, we employ two complementary methods: term suggestion and term relevance feedback. The experimental results show that our proposed system can alleviatl' semantic term mismatches and can also provide the appropriate similarity measurements. As a result, we know that our system can improve the rctrieval efficiency of the information retrieval system.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.53-72
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• 2007

This study is designed to assess whether storyboard surrogates are useful enough to be utilized for indexing sources as well as for metadata elements using 12 sample videos and 14 participants. Study shows that first, the match rates of index terms and summaries are significantly different according to video types, which means storyboard surrogates are especially useful for the type of videos of conveying their meanings mainly through images. Second, participants could assign subject keywords and summaries to digital video, sacrificing a little loss of full video clips' match rates. Moreover, the match rate of index terms (0.45) is higher than that of summaries (0.40). This means storyboard surrogates could be more useful for indexing videos rather than summarizing them. The study suggests that 1)storyboard surrogates can be used as sources for indexing and abstracting digital videos; 2) using storyboard surrogates along with other metadata elements (e.g., text-based abstracts) can be more useful for users' relevance judgement; and 3)storyboard surrogates can be utilized as match sources of image-based queries. Finally, in order to improve storyboard surrogates quality, this study proposes future studies: constructing key frame extraction algorithms and designing key frame arrangement models.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6697-6704
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• 2015

Background: The burden of breast and cervical cancer is changing over time in developing countries. Regular screening is very important for early detection and treatment. In this study, we assessed inequalities in breast and cervical cancer screening rates in women according to household wealth status, and analyzed the potential predictors associated with a low cancer screening rate in Jordan. Materials and Methods: A nationwide populationbased cross-sectional survey collected information on different variables at the national level. All ever-married women (the phrase is used throughout the text to refer to women who had ever married) aged 15-49 years were included in the survey. Analysis of breast self-examination (BSE) and clinical breast examination (CBE) at least once in the previous year was carried out in 11,068 women, while lifetime Pap-smear testing was carried out in 8,333 women, aged 20-49 years. Results: Over 39% and 19% of ever-married Jordanian women reported having undergone a breast examination during the previous year and Pap smear examination at least once in their lifetime, respectively. The rate of BSE in the previous year was 31.5%, that of CBE in the previous year was 19.3%, and that of Pap smear examination at least once in life was 25.5%. The adjusted OR was higher for performing BSE (aOR 1.22, 95% CI 1.04-1.43), undergoing CBE (aOR 1.31, 95% CI 1.08-1.60) and undergoing Pap smear examination (aOR 2.38, 95% CI 1.92-2.93) among women in the highest wealth-index quintile as compared to those in the lowest quintile. The concentration index was 0.11 for BSE, 0.01 for CBE, and 0.27 for Pap smear examination. Women in their twenties, living in rural or the southern region of Jordan, with an elementary school education or less, who listened to the radio or read the newspaper not more than a few times a year, and nulliparous women were less likely to undergo breast and cervical cancer screening. Conclusions: The rates of breast and cervical cancer screening are low in Jordan. Reducing the sociodemographic and economic inequalities in breast and cervical cancer screenings requires concerted outreach activities for women living under socially deprived conditions.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1145-1156
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• 2002

We propose a web document transcoding technique that translates existing web pages designed for desktop computers into an appropriate form for hand-held devices connected to the wireless internet. By defining a content block based on a visual separation and using it as a minimum unit for analyzing and converting processes, we can get web pages converted more exactly. We also apply the reallocation of the content block and the generation of new index in order to provide convenient interface without left-right scrolling in small screen devices. These methods, compared with existing ways such as text level summary or partial extraction method, can provide efficient navigation and a full recognition of web documents. To gain those transcoding benefits, we propose the Layout-Forming Tag Analysis Algorithm that analyzes structural tags, which motivate visual separation and the Component Grouping Algorithm that extracts the content block. We also classify and rearrange the content block and generate the new index to produce an appropriate form of web pages for small display devices. We have designed and implemented our transcoding system in a proxy server and evaluated the methods and the algorithms through an analysis of transcoded results. Our transcoding system showed a good result on most of popular web pages that have complicated structures.

• Journal of the Korean Chemical Society
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• v.63 no.2
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• pp.111-122
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• 2019

In this study, the characteristics of the reading materials in the chemistry domain of elementary school science and middle school science textbooks and chemistry I and II textbooks developed under the 2009 Revised National Science Curriculum were investigated. The criteria for classifying the reading materials were the types of theme, purpose, types of presentation, and students' activity. The inscriptions in the reading materials were also analyzed from the viewpoint of type, role, caption and index, and proximity type. The results indicated that more reading materials were included in the elementary science textbooks compared to middle school science, chemistry I, and/or chemistry II textbooks. The percentage of application in everyday life theme was high in the reading materials of elementary science textbooks, whereas the percentage of scientific knowledge theme was high in those of middle school science, chemistry I, and/or chemistry II textbooks. It was also found that the percentage of expanding concepts purpose was high in the reading materials of elementary science textbooks, whereas the percentage of supplementing concepts purpose was high in those of middle school science, chemistry I, and/or chemistry II textbooks. Several limitations in the use of inscriptions were found to exist; most inscriptions were photograph and/or illustration; most inscriptions were supplementing or elaborating texts; many inscriptions were presented without a caption or an index; there was a problem in the proximity of inscriptions to text.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.51-67
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• 2022

The purpose of this study is to diagnose the current status of alternative materials in Korea and to suggest directions and goals for the development of alternative materials. The comprehensive list of national alternative materials and the list of popular and new books were analyzed using the collection evaluation method. Results first the percentage of alternative material collections based on the popular book list for 10 years is 90.1%. The production rate of alternative materials is low in the subjects of 'Language', 'Art' and 'Technology and Science'. Most of the service formats were 'text only daisy'. Second, the CCHR(Common Collection Holding Ratio) and CUI(Collection Uniqueness index) of alternative materials were analyzed using the union catalog. Libraries with a large volume of books have a high proportion of CCHR and CUI. Topics with the highest CCHR are 'Literature' and 'Social Science'. The subjects with the highest collection uniqueness index are 'religion', 'art', and 'language'. Third, the replacement ratio of new books for 3 years is 5.09%. During the same period, the average book purchase rate of public libraries was 8.83%. The average book purchase rate in public libraries is 8.83%, and it is necessary to increase the collection rate of alternative materials based on this ratio.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.18-36
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• 2024

As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.