• Journal of Information Technology Applications and Management
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• v.23 no.1
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• pp.97-117
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• 2016

Drawing on the theoretical framework of customer value-satisfaction-loyalty, this study examines how scarcity message influences customers' value, satisfaction, and loyalty in the context of group-buying social commerce. Previous studies have argued that scarcity message limiting the avilability of products and service is a source of enhancing customer value. In this regard, this study posits scarcity message as a predictor of customer value. Furthermore, this study classifies customer value into two forms (i.e., utilitarian value and hedonic value) and verfies how scarcity message is associated with them. To test the proposed research model and hypotheses, this study performed structural equation modeling (SEM) analyses, using a total of 292 data collected on users who have experience in purchasing products and service through group-buying social commerce sites such as Coupang, Timon, and WeMakePrice. The key results are as follows : First, scarcity message increases utilitarian and hedonic values and further customer satisfaction. Second, utilitarian value increases customer satisfaction and repurchase intention while hedonic value has nothing to do with them. The findings imply that customers seek to maximize utilitarian value through group-buying social commerce. Finally, this study indicates that repuchase intention depends greatly on customer satisfaction.

• Journal of Fashion Business
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• v.19 no.4
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• pp.1-20
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• 2015

Acceleration of the fashion cycle has caused problems of environmental pollution because consumers made a lot of waste of clothes. To solve them, upcycle design has been uprised. This study researched the present condition through recent cases of upcycle design. The standard of collected cases is focused on used products which was already run out once and then has been recreated by being recreated with new design. Through this study, there is a purpose to provide solution of environmental pollutions and a right direction of upcycle fashion design. Collected cases are classified into five production methods. First method is Melting and Compressing, which it melts or compresses materials. Second method is Gathering and Combining, which it gathers or combines each different materials. Third method is Cutting and Dividing, which it cuts or divides products materials. Fourth method is Mixing and Changing, which it mixes materials, adds design elements, and changes of purpose. Final things are classified with multiplicatively used factors which are already divided.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.77-86
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• 2016

As the focus of game market moves to mobile era, payment on cyber money, specifically for Gacha system, possesses a large portion for creating profit in game industry. For this reason, this study mainly focuses on Puzzle and Dragon, the mobile game of Gungho online entertainment in Japan, which has made enormous profit for several years. The analysis on consumer sentiment for Gacha are categorized as below: (1) gambling mentality and cognitive error in stochastic game in God festival (2) reactional psychology for scarcity message in limited time God festival and collaboration (3) personal satisfaction through friend system and character collection.

• The Journal of Korean Association of Computer Education
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• v.19 no.1
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• pp.111-118
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• 2016

Measuring similarity in collaborative filtering-based recommender systems greatly affects system performance. This is because items are recommended from other similar users. In order to overcome the biggest problem of traditional similarity measures, i.e., data sparsity problem, this study suggests a new similarity measure that is the optimal combination of previous similarity and the value reflecting the number of co-rated items. We conducted experiments with various conditions to evaluate performance of the proposed measure. As a result, the proposed measure yielded much better performance than previous ones in terms of prediction qualities, specifically the maximum of about 7% improvement over the traditional Pearson correlation and about 4% over the cosine similarity.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.65-65
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• 2010

지구상의 광물, 암석, 화석 그리고 지질구조, 지형 등의 개개의 지형 지질학적 요소의 특성과 다른 대상과의 상호관계를 지질다양성이라고 한다. 지질다양성은 지형 지질에 내재되어 있는 본질적, 문화적, 심미적, 경제적, 기능적, 연구 및 교육적 가치를 이해하고 보전함으로써 유지 할 수 있다. 이 연구는 지질다양성에 대한 흥미와 이해를 높이기 위해 학술적 보전 가치가 있는 강원도 영월지역을 선정하여 그 특징을 분석하고 지질다양성을 효율적으로 활용하는 방안을 제언하고자 한다. 강원도 영월지역의 지질다양성에 대한 조사는 지형경관 자원과 지질특성의 희소성, 대표성, 학문적 가치 및 활용가치에 중점을 두고 전문가와 협의하여 보존가치가 있고 지리적으로 접근하기 편리한 노두 8곳을 선별하였다. 선별된 8곳의 노두는 고생대의 암석과 지층, 뚜렷한 퇴적구조, 화석, 규모가 크고 전형적인 하천지형이 나타나는 곳으로 지질유산(지형 지질)의 내재적 가치와 지구과학적 이해를 도울 수 있는 대상지이다. 대상지의 지질다양성에 대한 조사를 토대로 야외 지질학습장과 지질공원 및 지질명소, 과학적 특별흥미지역 등을 개발하여 제공함으로써 지형 지질에 대한 자기주도적 학습 능력 신장과 지구과학에 대한 흥미와 이해를 증진시키는 장을 마련해 줄 수 있을 것이다. 또한 과학적 가치와 더불어 사회적, 문화적 가치를 부여하여 보전함으로써 지질유산(지형 지질)에 대한 새로운 시각이 생길 것이다.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.573-580
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• 2001

The large amounts of high dimensional data contains a significant amount of noises by it own sparsity, which adds difficulties in high dimensional clustering. The CLIP is developed as a clustering algorithm to support characteristics of the high dimensional data. The CLIP is based on the incremental one dimensional projection on each axis and find product sets of the dimensional clusters. These product sets contain not only all high dimensional clusters but also they may contain noises. In this paper, we propose extended CLIP algorithm which refines the product sets that contain cluster. We remove high dimensional noises by applying two dimensional projections iteratively on the already found product sets by CLIP. To evaluate the performance of extended algorithm, we demonstrate its effectiveness through a series of experiments on synthetic data sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.461-467
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• 2003

We propose an efficient method for separable symmetric linear filtering in the DCT domain. First, separable 2-D linear filtering is decomposed into the cascade of 1-D filtering in the DCT domain. We investigate special characteristics of DCT domain filtering matrices when the filter coefficients are symmetric. Then we present the DCT domain 2-D filtering method using these characteristics. The proposed method requires smaller number of multiplications including typical sparseness of DCT coefficients compared to previous DCT domain linear filtering methods. Also, the proposed method is composed of simple and regular operations, which would be appropriate for efficient VLSI implementation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.7-13
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• 2011

While the TCP throughput degradation problem in coded wireless mesh networks is well-known, few effective solutions have been proposed. Most schemes proposed attempts to mask packet reordering by ordering packets at a lower layer or to adjust a packet transmission rate to solve the scarcity problem of coding opportunities. Through the throughput comparison of traditional standard TCP variants, we show that losses and duplication of TCP acknowledgements in coded wireless mesh networks can impact throughput. In addition, we show that a TCP variant that does not rely on duplicate acknowledgements is more suitable for coded wireless mesh networks.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.240-245
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• 2015

일반영역 음성인식은 n-gram 희소성 문제로 인해 대용량의 언어모델이 필요하다. 대용량 언어모델은 분산형 모델로 구현될 수 있고, 사용자 입력에 대한 동적 언어모델 보간 기술을 통해 음성인식 성능을 개선할 수 있다. 본 논문은 동적 언어모델 보간 기술에 대한 새로운 접근방법을 시도한다. 텍스트 군집화를 통해 주제별 언어모델을 생성한다. 여기서 주제는 사용자 입력 영역에 대응한다. 본 논문은 사용자 입력에 대하여 실시간으로 주제별 언어모델의 보간 가중치 값을 계산하는 접근 방법을 제시한다. 또한 언어모델의 보간 가중치 값 계산의 부담을 감소하기 위해 언어모델 군집화를 통해 대용량 언어모델 보간 접근 방법의 연산 부담을 해소하기 위한 시도를 한다. 주제별 언어모델에 기반하고 언어모델 군집화를 통한 동적 언어모델 보간 기술의 실험 결과 음성인식 오류 감소율 6.89%를 달성했다. 또한 언어모델 군집화 기술은 음성인식 정확도를 0.09% 저하시켰을 때 실행 시간을 17.6% 개선시키는 실험결과를 보였다.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.561-571
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• 2007

Local linear regression estimator is the most widely used nonparametric regression estimator which has a number of advantages over the traditional kernel estimators. It is well known that local linear estimator can produce erratic result in sparse regions in the realization of the design and the interpolation method of Hall and Turlach (1997) is the very efficient way to resolve this problem. However, it has been never pointed out that Hall and Turlach's interpolation method is very sensitive to outliers. In this paper, we propose the robust version of the interpolation method for adapting to sparse design. The finite sample properties of the method is compared with Hall and Turlach's method by the simulation study.