• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.17-26
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• 2014

This Paper discusses about the popularity of indie games that have recently caught spotlight from multiple platforms by finding the reason from the games' innovative way of interaction and new attempts in narrative style, and the objective is a preliminary study on indie games' game design, storytelling and it's prestige. This paper focuses on the aspects of indie games compared to established studio games by means of interaction mechanism, directing style and narrative style, and analyzed it with examples. In addition, it looks into examples of Korean indie games entering global platforms such as Steam.

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.75-85
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• 2017

Open innovation, a new paradigm which utilizes customer ideas for organizational innovation directly, is evaluated as a useful method to innovate the organization itself. In this research, we analyze the case of Starbucks' online community, MyStarbucksIdea.com to examine how collective intelligence is formed out of mass customers in the community and how open innovation is to be implemented successfully. We review various challenges in implementing open innovation and then suggest practical approaches to the challenges, including customer relationship management, utilization of opinion leaders, application of engineering techniques, etc.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.563-570
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• 2004

As the use of the Internet becomes more popular, a huge amount of information is published on the Web, and users can access the information effectively with Web search services. Since Web search services retrieve relevant documents from those collected by Web robots we need to improve the crawling quality of Web robots. In this paper, we suggest evaluation criteria for Web robots such as efficiency, continuity, freshness, coverage, silence, uniqueness and safety, and present various functions to improve the performance of Web robots. We also investigate the functions implemented in the conventional Web robots of NAVER, Google, AltaVista etc. It is expected that this study could contribute the development of more effective Web robots.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.338-347
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• 2018

This writing presents a structural methodology that conceptualize' Fransis Ford Coppola's perspective and adaptation style of his screenplay derived from the author Mario Puzo's original novel "The Godfather". This paper is divided into two different stages: The first stage, namely the "formal stage", encapsulates the analysis of narration and exploring the effects of structural transformations, such as deleting, creating and modifying from the novel to the screenplay. The second stage, entitled "semantic stage", is concerned with ascertaining the difference between the structure itself and the adapter's perspective on the original novel. The opening sequence of will be used as a case study to explore these issues in examining its adaptation style specifically while also offering a template for adapting a screenplay from a novel.

• Journal of Oriental Neuropsychiatry
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• v.31 no.4
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• pp.235-247
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• 2020

Objectives: In this study, we examine whether Sasang constitutions include all 8 attitude-function types, forming a complete paradigm from the perspective of Jungian psychological type theory. Methods: Analysis of the meanings of psychological attitudes and function of each Sasang constitution was performed, comparing them with the typological theories of C.G.Jung and John Beebe, both of whom are eminent minds in Jungian typology. Results and Conclusions: (1) Each Sasang constitution had all 8 psychological attitude-function combinations, which are diversely differentiated by type within their conscious and unconscious psyches. This is likely because attitudes and functions that develop in the conscious mind build up compensating attitudes and functions in the unconscious. (2) It seems that extroversion and introversion coexist within every Sasang constitution as psychological descriptions reported by Lee, Je ma state. The superior and inferior functions are disposed in the order of organ size in Sasang constitutions, but dominance of extroversion or introversion as defined by Jung's concepts of attitude does not seem to be determined by constitution.

• Journal of Dental Rehabilitation and Applied Science
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• v.33 no.1
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• pp.7-18
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• 2017

Purpose: Nonsteroidal anti-inflammatory drugs that prohibit biosynthesis of arachidonic acid metabolites have been considered potent host modulation agents. The aim of this review was to determine the effect of nonsteroidal anti-inflammatory drugs adjunctive with nonsurgical periodontal treatment in patients with periodontal disease. Materials and Methods: Three electronic databases were searched to identify relevant studies. The methodological quality and mean differences of the change in clinical attachment level and probing depth were analyzed according to Cochrane review methods. Results: Twelve studies were included in the methodological assessment and nine studies were suitable for inclusion in the meta-analysis. The mean difference in the clinical attachment level gain did not differ significantly between the nonsteroidal anti-inflammatory drugs and control groups at any observation time. The highest mean difference in clinical attachment level gain was 0.30 mm at 4 weeks (95% confidence interval = -0.37 to 0.97). There was a significant mean difference in the probing depth reduction, of 0.34 mm (95% confidence interval = 0.29 to 0.40) at 6 weeks. Conclusion: Therefore, nonsteroidal anti-inflammatory drugs have additional therapeutic effect when administrated with nonsurgical periodontal treatment.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.123-133
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• 2011

In this paper, we propose a new method for toon shading using 3D texture which renders 3d objects in a cartoon style. The conventional toon shading using 1D texture displays shading tone by computing the relative position and orientation between a light vector and surface normal. The 1D texture alone has limits to express the various tone change according to any viewing condition. Therefore Barla et. al. replaces a 1D texture with a 2D texture whose the second dimension corresponds to the view-dependent effects such as level-of-abstraction, depthof-field. The proposed scheme extends 2D texture to 3D texture by adding one dimension with the geometric information of 3D objects such as curvature, saliency, and coordinates. This approach supports two kinds of extensions for cartoon style diversification. First, we support "shape exaggeration effect" to emphasize silhouette or highlight according to the geometric information of 3D objects. Second, we further incorporate "cartoon specific effect", which is examples of screen tone and out focusing frequently appeared in cartoons. We demonstrate the effectiveness of our approach through examples that include a number of 3d objects rendered in various cartoon style.

• Journal of Information Management
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• v.18 no.4
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• pp.98-117
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• 1985

At the present time, the role and importance of information retrieval has greatly increased for two main reasons: the coverage of the searchable collections is now extensive and collection size may exceed several million documents; further more, the search results can now be obtained more or less instantaneously using online procedures and computer terminal devices that provide interaction and communication between system and users. The large collection size make it plausible to the users that relevant information will in fact be retrieved as a result of a search operation, and the probability of obtaining the search output without delay creates a substantial user demand for the retrieval services.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.11-20
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• 2024

Among the generative models in Artificial Intelligence (AI), especially Generative Adversarial Network (GAN) has been successful in various applications such as image processing, density estimation, and style transfer. While the GAN models including Conditional GAN (CGAN), CycleGAN, BigGAN, have been extended and improved, researchers face challenges in real-world applications in specific domains such as disaster simulation, healthcare, and urban planning due to data scarcity and unstable learning causing Image distortion. This paper proposes a new progressive learning methodology called Progressive Step Training (PST) based on the Auxiliary Classifier GAN (ACGAN) that discriminates class labels, leveraging the progressive learning approach of the Progressive Growing of GAN (PGGAN). The PST model achieves 70.82% faster stabilization, 51.3% lower standard deviation, stable convergence of loss values in the later high resolution stages, and a 94.6% faster loss reduction compared to conventional methods.