• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.91-107
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• 2023

With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.45-52
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• 2023

With the advent of deep learning, Artificial Intelligence (AI) technology has experienced rapid advancements, extending its application across various industrial sectors. However, the focus has shifted from the independent use of AI technology to its dispersion and proliferation through the open AI ecosystem. This shift signifies the transition from a phase of research and development to an era where AI technology is becoming widely accessible to the general public. However, as this dispersion continues, there is an increasing demand for the verification of outcomes derived from AI technologies. Causal AI applies the traditional concept of causal inference to AI, allowing not only the analysis of data correlations but also the derivation of the causes of the results, thereby obtaining the optimal output values. Causal AI technology addresses these limitations by applying the theory of causal inference to machine learning and deep learning to derive the basis of the analysis results. This paper analyzes recent cases of causal AI technology and presents the major tasks and directions of causal AI, extracting patterns between data using the correlation between them and presenting the results of the analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.72-78
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• 2009

The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.

• Journal of Platform Technology
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• v.9 no.4
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• pp.10-31
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• 2021

The digital tax, recently referred to as the Google tax was finally agreed at the 31st General Assembly of the OECD (October 8, 2021) with full support by 136 countries and will take effect from 2023. The purpose of this study is to analyze the digital tax prepared by the OECD for global MNEs, and to suggest the impacts on the Korean industry and to present the Korean governmental countermeasures. As the first study, we analyzed the international agreement on digital tax. In results, we found that even if global MNEs do not set up a business operation in overseas countries, if sales and profits are generated, 25% of the excess profit is borne as tax (pillar 1), and when MNEs do business in all the countries, they are liable to at least a 15% tax (pillar 2). We think that countries around the world have prepared a minimum countermeasure to protect their companies in anticipation that global MNEs will easily encroach on their markets in the future. As the second study, in order to discover the reason why the MNEs are so strong, we investigated the trends of Google and B2B SaaS companies in details. In results, we discovered that the global MNEs establishes a digital platform partnership ecosystem that enables them to enter foreign markets easily and expand rapidly. In conclusion, as a countermeasure for the Republic of Korea, governmental policies were proposed at the corporate (startup nurturing), industry, and national level respectively.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.770-778
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• 2007

Fish schooling or group moving in cyber underwater is a part of beautiful and familiar ecosystem. It is not so easy to present the behavior of fish crowd naturally as a computer animation. Thanks to development of computer graphics in entertainment industry, the numbers of digital films and animations is increased and the scenes of numerous crowd are shown to us. Though there are many studies on the techniques to process the behavior of crowd effectively and the developments of crowd behavioral systems, there is not enough study on the development for an efficient crowd behavioral simulator. In this' paper, we smartly present the types offish behavior in cyber underwater and make up for the weak points of time and cost. We develop the fish schooling behavior simulator for the contents of cyber underwater, automating fish behavioral types realistically and efficiently.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.4
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• pp.192-197
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• 2013

Road traffic noise barriers being used to reduce the noise, but the city surroundings inhibition, ecosystem disturbance, and it is difficult to maintain. Can enhance or complement the existing noise barrier performance, so that it is necessary to develop an electronic noise-reduction system In this paper, we proposed an electronic road noise reduction devices to reduce road noise for a DSP-based signal processing and analog signal input-output controller. In order to verify the control performance, we performed noise reduction experimentation of ANC by filtered-X LMS algorithm and traffic noise signal injection. The controller is equipped with noise reduction algorithms were tested on the characteristics of directional and omnidirectional speaker.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.1-25
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• 2022

The financial MyData service has implemented in January 2022 and launched 45 services by banks, securities, credit cards and fintech companies. This study applied the Q methodology, to identify the user types of MyData services and compared the perceptions of employees of financial institutions who plan and develop the MyData services. There are three types of MyData service users: active users, limited users who focus on consumption and asset status inquiry, and sensitive users for personal information. There were two types of recognition of financial company employees. One is the active user support other is the sensitive user for personal information support. The analysis of subjective perceptions can be used as a reference for establishing a company's MyData service marketing strategy and establishing related policies to improve the MyData ecosystem.

• Journal of Information Technology Applications and Management
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• v.29 no.3
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• pp.75-93
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• 2022

The purpose of this study is to compare and analyze each government's ICT SME support policies to cope with changes in the ICT ecosystem paradigm. In particular, the core policies and policy trends of the Moon's government are presented through keyword network analysis and cognitive map analysis. As a result, core technologies such as ICT(Information Communication Technology), AI(Artificial Intelligence), Big Data, and 5G, which have high values of betweenness centrality and closeness centrality, are major keywords with high propagation power. The cognitive map analysis shows that the opportunity factors for the 4th industrial revolution are being activated through the ICT infrastructure circulation process, the domestic market circulation process, and the global market circulation process. This study is meaningful in terms of cognitive map analysis and utilization based on scientific analysis.

• Electronics and Telecommunications Trends
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• v.38 no.2
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• pp.75-84
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• 2023

Metaverse is expected to bring many innovations to society, culture, and economy by providing realistic services in various fields while suppressing time and space constraints. However, unclear definitions owing to the high diversity of the metaverse add to the confusion of the ecosystem participants. The current metaverse service has many voices of concern owing to technical limitations and lack of a clear profit model. Nevertheless, given its high growth potential driven by the digital transformation, a solid and long-term technology development strategy seems to be necessary. Accordingly, we analyze development cases centering on the major metaverse service shapes presented in the Metaverse New Industry Leading Strategy announced by the Ministry of Science and ICT in January 2022. In addition, we study the characteristics and core technologies of each metaverse service for its realization and discuss future stages of technological development.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.101-103
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• 2023

With the recent advances in communication technology and Internet of Things (IoT) infrastructure, home automation systems have emerged as a new paradigm for providing users with convenient smart home services. The IoT ecosystem has merged digital systems with the physical world, dramatically changing the way people live and work. However, at the same time, security remains one of the most significant research issues in IoT, as the deployment and application of high-availability systems come with various security risks that cause serious threats to users. Among them, the security issues arising from the interaction among devices/applications should not be underestimated. Attackers can exploit interactions among devices/applications to hack into the user's home. In this paper, we present a survey of research on detecting various types of interactions among devices/applications in IoT.