• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.147-153
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• 2023

As it spreads to all industries of artificial intelligence technology, AIaaS equipped with artificial intelligence services is emerging. In particular, non-IT companies are suffering from the absence of software experts, difficulties in training big data models, and difficulties in collecting and analyzing various types of data. AIaaS makes it easier and more economical for users to build a system by providing various IT resources necessary for artificial intelligence software development as well as functions necessary for artificial intelligence software in the form of a service. Therefore, the supply and demand for such cloud-based AIaaS services will increase rapidly. However, the quality of services provided by AIaaS becomes an important factor in what is required as the supply and demand for AIaaS increases. However, research on a comprehensive and practical quality evaluation metric to measure this is currently insufficient. Therefore, in this paper, we develop and propose a usability, replacement, scalability, and publicity metric, which are the four metrics necessary for measuring reusability, based on implementation, convenience, efficiency, and accessibility, which are characteristics of AIaaS, for reusability evaluation among the service quality measurement factors of AIaaS. The proposed metrics can be used as a tool to predict how much services provided by AIaaS can be reused for potential users in the future.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.519-531
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• 2020

Global warming is accelerating as greenhouse gas emissions increase owing to the increase in population and urbanization rates worldwide. As an alternative to this solution, smart cities are being promoted. The purpose of this paper is to suggest a plan for developing energy service modules for the Sejong 5-1 living area, which has been selected as a test-bed for smart cities in Korea. Based on the smart city plans announced by the government for this study, a survey questionnaire on 12 energy services was composed by collecting the opinions of experts. The survey was conducted with 1,000 citizens, the degree of necessity of energy service that citizens think of was identified. Principal Component Analysis and Association Rule Mining were conducted to describe 12 energy service items in a reduced manner and analyze the correlation and relationship of each energy service. Finally, three modules were suggested using the analyzed results so that 12 energy services could be implemented in an efficient platform. These results are expected to contribute to the realization of a smart city to make them easily accessible for those who want to promote platform services in the energy field and envision energy service items.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.394-399
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• 2016

This study examines how the patent results of the University Academic-Industrial Cooperation influence technology transfer. Statistical analysis was performed by using 2013 panel data from the Ministry of Education and Science Technology(MEST) National Research Foundation of Korea(NRF) and the results are as follows. The results show that the patent result factors that have a positive effect on the total number of technology transfers are domestic patent application numbers, foreign patent application numbers, future technology(6T) patent application numbers, science technology patent application numbers. The factors that have a positive effect on increasing royalty are the total number of technology transfers. Domestic patent application numbers, future technology(6T) patent application numbers and science technology patent application numbers have a positive effect on patent results. The results implicate that more research and development is needed for more patents to be applied, that the main focus should be on future technology(6T) and science technology fields, and that effort should be directed at planning negotiation strategies for the term of the contract. However, this study is the need to research, including primary research is so patent performance may be limited in having only been considered in future studies of human and material resources and operating system factors that may be presented to the essential elements of the Industry-Academic Cooperation Foundation this raises.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.78-83
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• 2003

본 연구에서는 건설CALS/EC 기반의 정보화 추진을 위한 정보시스템을 개발할 때 적용되는 기존의 소프트웨어 개발방법론의 문제점을 분석하고, 표준화되지 않은 개발방법론의 적용으로 시스템 개발에 비효율적인 비용을 투자하는 문제점과 특성상 입찰, 구매, 계약 등 분야별로 상이한 기능의 업무에 따라 구축되는 건설산업 정보화에 있어서 상호간에 데이터 및 프로세스를 원활히 통합하지 못하므로 인하여 발생되는 개발의 중복성, 정보 활용의 비효율성 등의 문제점을 개선하고자 하였다. 이를 위하여 최근 새로이 부각되고 있는 방법론인 컴포넌트 기반 개발방법론(CBD: Component-Based Development)을 사용하여 건선CALS/EC 표준지침 웹서비스를 위한 시스템의 업무프로세스를 모델링하여 사용자가 쉽게 재사용가능하고 타업무분야에 확대 가능한 방향을 제시하였다. 본 연구를 위하여 기존의 소프트웨어 개발 방법론의 적용상 문제점 분석을 통하여 컴포넌트 기반 개발방법론의 필요성을 증명하고 비즈니스 컴포넌트 프레임워크를 사용하여 건설 CALS/EC 표준지침 웹서비스의 업무프로세스에 적용할 기술적인 방법론을 고찰하고 업무에 효과적으로 적용할 수 있는 업무프로세스 컴포넌트를 제시하였다. 본 연구에서 도출된 컴포넌트 모델은 향후 타업무분야의 시스템을 개발할 때 사용자요구분석 단계부터 별도의 재 작업이 없이 사용될 수 있으며 시스템을 구현할 때 개발 모듈의 중복방지와 용이한 비즈니스로직의 변경 등이 가능하며, 추가의 업무 프로세스나 연관된 다른 분야의 업무프로세스의 반영 및 추가 시 컴포넌트의 활동모델을 쉽게 수정하여 정의함으로써 쉽게 시스템의 기능을 확장할 수 있다.LE 산정에 관한 지속적인 실험적 연구가 이루어져야 하겠다. 증가할 것이다. 또한 부분육을 이용한 완전제품, 적색육제품, 유기농이나 별미식 제품과 같은 형태의 다양한 포장육 제품이 도입 될 것으로 생각되어진다.e in vitro SPF test method will be able to be used as an alternative method for in vivo SPF in case of lotion and cream. replica. A statistically significant improvement of Star Fruit Leaf Extract BG30-treated site was seen in decreased wrinkles. Star Fruit Leaf Extract BG30 results in clinically visible improvement in wrinkling when used topically for 5 weeks. 또한 관계마케팅, CRM 등의 이론적 배경이 되고 있는 신뢰와 결속의 중요성이 재확인하는 결과도 의의라고 할 수 있다. 그리고 신뢰는 양사 간의 상호관계에서 조성될 수 있는 특성을 가진 반면, 결속은 계약관계 초기단계에서 성문화하고 규정화 할 수 있는 변수의 성격이 강하다고 할 수가 있다. 본 연구는 복잡한 기업간 관계를 지나치게 협력적 측면에서만 규명했기 때문에 많은 측면을 간과할 가능성이 있다. 또한 방법론적으로 일방향의 시각만을 고려했고, 횡단적 조사를 통하고 국내의 한 서비스제공업체와 관련이 있는 컨텐츠 공급파트너만의 시각을 검증했기 때문에 해석에서 유의할 필요가 있다. 또한 타당성확보 노력을 기하였지만 측정도구

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.247-253
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• 2011

In 2009, the Korean international construction industry showed a great performance, totaling 49.1 billion of contract and then this achievement has been considered a key milestone presenting that the international construction industry is one of the primary export industries of Korea. However, because of the construction firms' equalized levels of technology and price competitiveness, the competition among bidders is becoming more intensive. Moreover, this changing market circumstance leads construction firms to apply for bidding with the lowest price that could not meet the expected profitability of a project. Therefore, to develop various strategies based on project characteristics becomes one of the critical capabilities that construction firms should possess. Based on these motives, this study is aimed to investigate associations among number of bidders, contract award rate, profitability on international projects. For the correlation analysis, a set of data is structured by collecting all projects ranging from 1993 to 2009, excluding projects funded by official development and domestic funds. The number of bidders were grouped depending on project characteristics such as market regions, project types, bidding types, and order organization types. As the result of correlation analysis, contract award rate increases as the number of bidders increase, but the relationship between the number of bidders and profitability is negative. Understanding the correlations among variables can be employed in developing strategies to improve construction firms' competitiveness in the international construction market.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.21-31
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• 2014

In this article, data mining simulation is applied to find a proper approach and results of analysis for study of variables related to organization. Also, turnover intention and organizational commitment are used as target (dependent) variables in this simulation. Classification and regression tree (CART) with ensemble methods are used in this study for simulation. Human capital corporate panel data of Korea Research Institute for Vocation Education & Training (KRIVET) is used. The panel data is collected in 2005, 2007, and 2009. Organizational commitment variables are analyzed with combined measure variables which are created after investigation of reliability and single dimensionality for multiple-item measurement details. The results of this study are as follows. First, major determinants of turnover intention are trust, communication, and talent management-oriented trend. Second, the main determining factors for organizational commitment are trust, the number of years worked, innovation, communication. CART with ensemble methods has two ensemble CART methods which are CART with Bagging and CART with Arcing. Comparing two methods, CART with Arcing (Arc-x4) extracted scenarios with very high coefficients of determination. In this study, a scenario with maximum coefficient of determinant and minimum error is obtained and practical implications are presented. Using one of data mining methods, CART with ensemble method. Also, the limitation and future research are discussed.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.115-125
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• 2020

Problem-Based Learning is the most commonly used teaching method in the field of education as the demand for talented people with creative problem-solving abilities has increased in recent society. In this study, we developed a tool that can simply and regularly measure the learning effects of applying Problem-Based Learning on the classroom. Twenty-two preliminary items for the development were constructed by gathering expert opinions about items collected in existing research of Problem-Based Learning effects measurement. Using this preliminary items, data were collected from 124 students who took the subject-based study. And the validity and reliability were verified through Rash analysis. 11 of 124 students and 1 of 22 items were found to nonconforming and excluded. In addition, the optimal scale for the configuration of this tool was found to be a four-point scale, and the reliability of separation on the subject and the item was found to be excellent. We hope that the assessment tools of Problem-Based Learning effectiveness developed in this study will be actively used to measure learning effectiveness and manage the quality of education.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.109-128
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• 2010

The purpose of our research is to figure out the 'non-financial value' of consumers applying networks amongst consumer groups, the data-based marketing strategy to the analysis and delve into the ways for enhancing effectives in marketing activities by adapting the value to the marketing. To verify the authenticity of the points, we did the empirical test on the consumer group using 'the Essence Cosmetics Products' of high involvement that is deeply affected by consumer perceptions and the word-of-mouth activities. 1) The empirical analysis reveals the following features. First, the segmented market for 'Essence Consumer' is composed of several independent networks, each network shows to have the consumers that is high degree centrality and closeness centrality. Second, the result proves the authenticity of the non-financial value for boosting corporate profits by the high degree centrality and closeness centrality consumer's word-of-mouth activities. Lastly, we verify that there lies a difference in the network structure of 'Essence Cosmetics Market'per each product origin(domestic, foreign) and demographic characteristics. It does, therefore, indicate the need to consider the features applying mutually complementary for the network targeting.