• Journal of Digital Convergence
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• v.21 no.2
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• pp.27-32
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• 2023

This study is about a marketability analysis and commercialization methodology analysis system using big data, and a marketability analysis and commercialization methodology analysis system that can analyze the marketability of the product based on a content channel capable of viral marketing. The marketability analysis and commercialization methodology analysis system using big data according to this study analyzes the marketability of the products to be analyzed by analyzing the marketing content provided on the content channel, so it has the advantage of determining more accurate viral marketing effects on the products to be analyzed.

• Journal of the Korean Society of Costume
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• v.59 no.9
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• pp.146-162
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• 2009

In the current product and fashion design, the 'eco-friendliness' is affecting practically and conceptually on all the sectors of industry and culture. Therefore, this study seeks to examine specific values in the concept of eco-friendly design. The subjects of this paper are studied on the scholarly journals, and are confined to those from 1990, when naturalism and ecology trend started to be in product and fashion, to the moment of search of February 2009. This study used 'Naturalism', 'Green', 'Environment-friendly', 'Eco', 'Sustainable', 'Well-being' and 'Lohas' as key words for the search. Analysis is performed by content analysis and the unit of analysis was based upon the adjectives, nouns and phrases which is related key words in the concept of eco-friendly design. The study realized that there are personal value, environmental value, economic value, and social value in the concept of eco-friendly design. In the result, it is not enough to consider the effect on environment only. Understanding the personal, environmental, economic, and social value from the viewpoint of customers, finding the optimal design factors, and reflecting them in development of product and fashion are necessary to pave the way for advanced eco-friendly design. The results of this paper would help to the future product and fashion development for eco-friendly brands.

• Journal of the Korean Society for information Management
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• v.37 no.2
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• pp.225-249
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• 2020

The purpose of this study is to identify and systematize various facet elements required by users in fiction search situations from book tags to improve the fiction search environment. Based on the Ranganathan's PMEST formula, the basic facet system of the fiction was defined as 1) the personality that forms the fiction material, 2) the content and external characteristics that compose the fiction, 3) the reader interaction with books, 4) spatial information related to fiction and reading activities, and 5) time information related to fiction and reading activities. Out of approximately 310,000 tags assigned to 7,174 fiction, 3,730 core tags were selected and content-analyzed. As a result, various attributes were systematized around the top 25 categories of the fiction facets. The results of this study can be applied to facet navigation of OPAC and fiction DB in the future.

• The Journal of Bigdata
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• v.4 no.2
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• pp.23-34
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• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• Journal of Nutrition and Health
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• v.35 no.1
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• pp.115-123
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• 2002

This study was carried out to investigate the utilization status of internet dietary information by gender(boys: 363, girls: 366) in adolescent(middle & high school students). The results were summarized as follows. The internet using frequency of 6-7times per week had 45.0% of subjects and the using time of internet per a time was shown mainly'<2hours(68.5%)'. The main place for internet use was home(79.0%) and favorite search engine was 'Yahoo'(45.7%) and 'Daum'(19.3%). As main purpose using internet were mentioned 'social intercourse'(45.0%) and data search'(24.8%). The organization that offer to reliable internet information was educational institution'(49.4%). The problems in using information site were 'poor information'(26.4%), 'slow connection speed'(22.6%), and 'don't arouse interest'(18.8%). The search experience about dietary information had only 27.9% of subjects and search purpose was 'for homework'(33.3%) and 'for health'(32.0). The satisfaction degree of dietary information was not high. The connection motive to dietary information was mainly 'by site navigation casualty'(55.7%). Only 7.7% of subjects had experience of nutrition counseling using internet, and the motive of nutrition counseling was also 'by site navigation causally'(55.8%). The purpose of counseling was 'for diet'(41.5%) and 'for health problem'(30.2%), and the satisfaction degree of counseling result was very low. As the ask of improvement for counseling site were pointed out 'poor in answer content'(44.8%) and 'lazy answer'(31.0%). The subjects wanted to get the dietary information about 'growth in status'(41.4%), 'diet related skin beauty'(14.6%), the update period less 1 month, and the way of 'free board'(32.3%), 'game'(21.1%) and 'animation'(19.3%) as offer tool. The results of this study showed that although the internet using percent and frequency of subjects was high, they used dietary information very seldom and they are dissatisfied with internet nutritional information. Therefore, the information donor should consider which dietary information was needed and what is the optimal tool for adolescent.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.65-72
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• 2018

Purpose - One of the biggest problems in the e-learning distribution process is the lack of quality content and learners' discredit in e-learning content. In order to respond to the various demands of the corporate education field appropriately, it is necessary to search for directions of new e-learning models that are out of traditional e-learning contents. The purpose of this study is to identify recent trend issues related to corporate e-learning and to suggest directions for development. Research design, data, and methodology - Based on the literature review, trend issues that should be considered important in corporate e-learning were derived. Online survey was conducted to evaluate the importance-feasibility of each issue to 13 experts on e-learning and corporate education. The contents of the questionnaire are as follows: 1) recognition of importance and feasibility of trend issues to be considered important in the future corporate education field; 2) factors to be considered in developing future e-learning contents. Results - Six trends derived from a comprehensive literature review. The most important e-learning trends for corporate education field were 'mobile learning', 'micro learning', 'blended learning', 'social learning', 'adaptive learning', 'engaged learning'. As a result of evaluating the importance and feasibility of each issue, experts point out that 'mobile learning' and 'micro learning' should be actively considered for introduction and utilization at present. In addition, 'social learning' and 'blended learning' need to be actively considered in the near future. On the other hand, experts recognized that 'adaptive learning' and 'engaged learning' need to be prepared from a long-term perspective. Conclusions - There are two main reasons for this result. First, in corporate e-learning, it is important to 1) be able to update on time, 2) the connection with the workplace is important. Second, it requires realistic verification of the expected performance of the learning model. To be considered part of the future are as follows: First, the value and effectiveness of the new e-learning type should be studied. Seconds, e-learning contents should be developed through adopting SAM or Agile methodology. Through this process, we would be able to enhance the quality in e-learning content.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.197-206
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• 2019

The purpose of this study is to identify trends of academic research on senior employment projects. For this aim, research results were collected from keyword searches utilizing academic search engines, and a total of 133 research studies were selected as analysis subjects. Then, we analyzed research trends such as sources, research themes, research methods, and research subjects using the content analysis method,. According to the results, the leading type of senior employment research was quantitative research that confirmed the effects of projects by targeting the elderly participants. On the other hand, there were relatively few cases in which philosophical and ethical reviews were used to understand the labor and social roles of the elderly in connection with senior employment projects. Based on these research trends, this study criticized the situation where not only a variety of main participants but also the elderly taking part in the senior employment project were excluded from the main concern of research and suggested that it was necessary for follow-up studies to emerge from these trends.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.43-49
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• 2024

In early 2020, as the COVID-19 pandemic hit the world, widespread changes occurred throughout society. COVID-19 also brought changes in consumers' consumption behaviors and preferences. This study aims to find out how the current status of the tourism industry and the coffee industry has changed since the end of COVID-19 by conducting big data analysis focusing on the search frequency of Naver, Google, and the following, which are representative social networks in Korea. Designating "Coffee Industry + Tourism Industry" as the representative keyword, January 1, 2020 to December 31, 2020, the time of each COVID-19 outbreak, was set before the COVID-19 type, and January 1, 2023 to December 31, 2023 was set after the end of COVID-19. Based on the analyzed search binder big data analysis within the period, we would like to find out how the current status of the tourism industry and the coffee industry has changed since the end of COVID-19. Finaly, the coffee and tourism industries are on the path of recovery and growth. In particular, the rise in coffee consumption, the recovery of the number of tourists, the emphasis on local tourism, and the strengthening of links with global markets are prominent.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.95-99
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• 2010

Social media refers to the content, which are created by users, such as blogs, social networks, and wikis. Recently, question-answering (QA) communities, in which users share information by questions and answers, are regarded as a kind of social media. Thus, QA communities have become a huge source of information for the past decade. However, it is hard for users to search the exact question-answer that is exactly matched with their needs as the number of question-answers increases in QA communities. This paper proposes an approach for classifying a question into three categories (information, opinion, and suggestion) according to the purpose of the question for more accurate information retrieval. Specifically, our approach is based on modified Na$\ddot{i}$ve Bayes classifier which uses structural characteristics of QA documents to improve the classification accuracy. Through our experiments, we achieved about 71.2% in classification accuracy.