• ETRI Journal
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• 제34권2호
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• pp.292-295
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• 2012

Beyond the simple keyword matching methods in contextual advertising, we propose a rich contextual matching (CM) model adopting a classification method for topic targeting and a query expansion method for semantic ad matching. This letter reports on an investigation into the empirical effects of the CM model by comparing the click-through rates (CTRs) of two practical online news advertising systems. Based on the evaluation results from over 100 million impressions, we prove that the average CTR of our proposed model outperforms that of a traditional model.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 2부
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• pp.158-164
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• 2008

본 논문은 모바일폰의 사용성 연구에 있어서 모바일폰의 사용 특성을 충분히 반영할 수 있도록 추후 연구를 돕기 위한 목적으로 진행되었다. 모바일폰의 사용 특성은 무엇보다 컨텍스의 영향에 매우 민감하다는 것과, 1인 1디바이스로서 개인적인 라이프 패턴을 많은 부분 수용한다는 것이다. 이러한 전제로부터 모바일폰이 사용되는 컨텍스트를 정의하였다. 특별히 컨텍스트의 정의에 있어서 상황적 컨텍스트(situational context)라는 정의를 도입하였으며, 모바일폰으로 할 수 있는 다양한 task 중 특별히 situational context의 영향을 직접적으로 받는 task를 contextual task로 이름하였다. 연구 결과물로써 contextual task의 모델을 제작하였다. 이는 디자인 종사자들과 타 업계의 종사자들이 모두 사용자의 실제적 행태를 이해할 수 있도록 하여 동일한 컨셉을 가지고 사용자 중심의 디자인을 진행할 수 있도록 한다. 또한, 이러한 사용자 사용 행태에 대한 통일한 컨셉은 디자인을 위한 서로의 의사전당에도 효과적일 젓이다. 수집된 사용자 task 들은 3가지 모델로 그 패턴을 정의할 수 있다. 사용자의 공간 확장과 관련되어 다양한 패턴을 구조화한 Extend Model, 기능의 컨버전스로 인해서 각 기능의 충돌을 최소화하여 사용성을 높일 수 있는 기회를 제공하기 위해 이와 관련된 task 들의 패턴을 구조화한 Synchronize Model, 마지막으로 사용자의 라이프 패턴을 반영하여 기존의 object를 대체하는 결과를 가져오는 task들의 패턴을 구조화한 Replace Model 로 Contextual Task를 정의하였다. 마지막으로 각 모델의 구체적 용도를 보이기 위해 Context 를 반영한 Interview 를 시행할 수 있는 질문지 제작을 진행하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.535-538
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• 1990

The main problem in speech recognition is the enormous variability in acoustic signals due to complex but predictable contextual effects. Especially in plosive consonants it is very difficult to find invariant cue due to various contextual effects, but humans use these contextual effects as helpful information in plosive consonant recognition. In this paper we experimented on three artificial neural net models for the recognition of plosive consonants. Neural Net Model I used "Multi-layer Perceptron ". Model II used a variation of the "Self-organizing Feature Map Model". And Model III used "Interactive and Competitive Model" to experiment contextual effects. The recognition experiment was performed on 9 Korean plosive consonants. We used VCV speech chains for the experiment on contextual effects. The speech chain consists of Korean plosive consonants /g, d, b, K, T, P, k, t, p/ (/ㄱ, ㄷ, ㅂ, ㄲ, ㄸ, ㅃ, ㅋ, ㅌ, ㅍ/) and eight Korean monothongs. The inputs to Neural Net Models were several temporal cues - duration of the silence, transition and vot -, and the extent of the VC formant transitions to the presence of voicing energy during closure, burst intensity, presence of asperation, amount of low frequency energy present at voicing onset, and CV formant transition extent from the acoustic signals. Model I showed about 55 - 67 %, Model II showed about 60%, and Model III showed about 67% recognition rate.

• 복식문화연구
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• 제25권3호
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• pp.327-339
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• 2017

A consumer is an individual entity with various motivations. This study is intended to incorporate a hierarchical structure of motivation to understand self-determined motivation for purchasing secondhand merchandise at thrift stores. A conceptual model adopted from Cadwallader et al. (2010)'s comprehensive model of motivation used in a marketing context was developed to investigate motivational process in secondhand merchandise shopping. The conceptual model includes the three levels of motivational structure-the global, contextual (environmental concern and frugality), and situational motivation. A series of the causal relationships among the three levels of self-determined motivations and buying intention to shop at thrift stores were hypothesized. A total of 219 respondents from two different northeastern state universities in the U.S. completed a self-administered survey. The results indicated that secondhand merchandise shopping is well explained in the hierarchical structure of self-determined motivation where the global motivation had a positive impact on the contextual motivations regarding environmental concern and frugality. Of the two contextual motivations, only environmental concern had a positive impact on situational motivation for shopping at thrift stores. Finally, the situational motivation positively influenced the intention to shop at thrift stores. The results of this model suggest that the hierarchical structure of self-determined motivation would be a very useful framework to understand consumer behavior for apparel shopping. Also, further research can be done to identify other contextual motivational factors to understand consumer motivation for shopping at thrift stores.

• Asia pacific journal of information systems
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• 제15권3호
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• pp.41-64
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• 2005

The effects of information quality and the importance of information have been reported in the information Systems(IS) literature. However, little has been learned about the impact of data quality(DQ) on decision performance. Recognizing with this problem, this study explores the effects of contextual DQ on decision performance. To examine them, a laboratory experiment was conducted. Based on two levels of contextual DQ and two levels of task complexity, this study had a $2{\times}2$ factorial design. The dependent variables used to measure the outcomes of decision performance were problem-solving accuracy and time. The results demonstrated that the effects of contextual DQ on decision performance were significant. The findings suggest that decision makers can expect to improve their decision performance by enhancing contextual DQ. This research not only extends a body of research examining the effects of factors that can be tied to human decision-making performance, but also provides empirical evidence to validate and extend DeLone and McLean's IS success model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3168-3186
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• 2020

Automatic topic essay generation (TEG) is a controllable text generation task that aims to generate informative, diverse, and topic-consistent essays based on multiple topics. To make the generated essays of high quality, a reasonable method should consider both diversity and topic-consistency. Another essential issue is the intrinsic link of the topics, which contributes to making the essays closely surround the semantics of provided topics. However, it remains challenging for TEG to fill the semantic gap between source topic words and target output, and a more powerful model is needed to capture the semantics of given topics. To this end, we propose a pretraining-based contextual self-attention (PC-SAN) model that is built upon the seq2seq framework. For the encoder of our model, we employ a dynamic weight sum of layers from BERT to fully utilize the semantics of topics, which is of great help to fill the gap and improve the quality of the generated essays. In the decoding phase, we also transform the target-side contextual history information into the query layers to alleviate the lack of context in typical self-attention networks (SANs). Experimental results on large-scale paragraph-level Chinese corpora verify that our model is capable of generating diverse, topic-consistent text and essentially makes improvements as compare to strong baselines. Furthermore, extensive analysis validates the effectiveness of contextual embeddings from BERT and contextual history information in SANs.

• Investigative Magnetic Resonance Imaging
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• 제3권2호
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• pp.179-187
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• 1999

목적 : 본 논문은 Bayes의 복합 의사결정모델을 이용한 효과적인 다중에코 자기공명영상의 분류방법을 소개한다. 동질성을 갖는 영역 혹은 경계선부위 등 영역을 명확히 분할하기 위하여 영상 내 국소 부위 이웃시스댐상의 주변정보(contextual information)를 이용한 분류 방법을 제시한다. 대상 및 방법 : 통계학적으로이질적 성분들로 구성된 영상을 대상으로 한 주변정보를 이용한 분류결과는 영상내의 국소적으로 정적인 영역들을이웃화소시스탬 내에서 정의되는 상호작용 인자의 메커니즘에 의해 분리함으로서 개선시킬 수 있다. 영상의 분류과정에서 분류결과의 정확도를 향상시키기 위하여 분류대상화소의 주변화소에 대한 분류패턴을 이용한다면 일반적으로 발생하는 분류의 모호성을 제거한다. 그러한 이유는 특정 화소와 인접한 주변의 데이터는 본질적으로 특정 화소와 상관관계를 내재하고 있으며, 만일 주변데이터의 특성을 파악할수 있다면, 대상화소의 성질을 결정하는데 도움을 얻을 수 있다. 본 논문에서는 분류 대상화소의 주변정보와 Bayes의 복합 의사결정모델을 이용한 context-dependent 분류 방법을 제시한다. 이 모델에서 주변 정보는 국소 부위 이웃시스댐으로부터 전이확률(tran­s sition probability)을 추출하여 화소간의 상관관계의 강도를 결정하는 상호인자 값으로 사용한다. 결과 : 본논문에서는 다중에코자기공명영상의 분류를 위하여 Bayes의 복합 의사결정모델을 이용한 분류방법을 제안하였다. 주변 데이터를 고려하지 않는 context-free 분류 방법에 비하여 특히 동질성을 강는 영역 혹은 경계선 부위 등에서의 분류결과가 우수하게 나타났으며, 이는 주변정보를이용한 결과이다. 결론 : 본 논문에서는클러스터링 분석과 복합 의사결정 Bayes 모델을 이용하여 다중에코 자기공명영상의 분류 결과를 향상시키기 위한 새로운 방법을 소개하였다.

• 산경연구논집
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• 제13권5호
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• pp.27-40
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• 2022

Purpose: Research on job crafting has thus far focused on how alter job demand and resources behaviors relate to employee task performance. However, job crafting behaviors do not necessarily have an impact only on task performance, but also on employees' contextual performance, a phenomenon that has little research in job crafting research. Therefore, this study aims to investigate the effect of job crafting on task performance or contextual performance and the mediating effect of work engagement between them in the Chinese context. Research design, data and methodology: In order to achieve the above research goals and test the proposed hypotheses, we used a cross-sectional design and a self-administered questionnaire to collect quantitative data from September 8, 2021 to September 27, 2021 among knowledge workers in Shandong Province various financial companies and finally analyzed 211 questionnaires. Descriptive statistics and research model analysis were performed using SPSS 25.0 Version and AMOS 27.0 Version to test the developed hypotheses. Results: The results are as follows; firstly, the study showed that job crafting of employees had a significant positive impact on task performance and contextual performance. Secondly, the higher job crafting of employees, the higher their work engagement. Thirdly, this study showed that work engagement of employees had a positive impact on task performance and contextual performance. Fourthly, we predicted and found that work engagement of employees had a positive mediating effect between job crafting and task performance and a positive mediating effect between job crafting and contextual performance. Overall, this study showed that the proactive job crafting behaviors of employees enhance their engagement for their work, which in turn improves task performance and contextual performance. Conclusions: This paper develops job crafting research by exploring the positive impact of job crafting on employees' task performance or contextual performance through their work engagement. It also proposes that both job crafting behaviors and work engagement are important approaches to improve employees' task performance or contextual performance. Practical implications for organizations, such as increasing employee' work engagement, as well as the limitations and suggestions are concluded for the future research directions.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.1052-1057
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• 1994

Dynamically localized self-organizing map model (DLSMM) is a new speech recognition model based on the well-known self-organizing map algorithm and dynamic programming technique. The DLSMM can efficiently normalize the temporal and spatial characteristics of speech signal at the same time. Especially, the proposed can use contextual information of speech. As experimental results on ten Korean digits recognition task, the DLSMM with contextual information has shown higher recognition rate than predictive neural network models.

• 보건교육건강증진학회지
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• 제28권4호
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• pp.1-14
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• 2011

Objectives: The aim of the present study is to elucidate the relationship of community capacity to health in a metropolitan area in Korea. To do so, a multi-level model to verify the contextual effects of community capacity is presented. Methods: The study materials are the "The 4th Seoul Citizens Health Indicators Surveys" on 404 dong in Seoul. The community capacity indicators were developed in two strata: individual-level indicators with community identity domain; and community-level indicators with participation in community organizations, number of non-profit organizations, degree of organizing of community-based organizations, and volunteer activities. Results: Higher unhealthy probability occurs among those with lower community capacity at the community level, lower individual income, and lower community satisfaction at the individual level. It contributed to explaining self-rated health status and showed that there were contextual effects of the community going beyond the compositional effects of the individual. Conclusions: In the process of building community capacity, a community autonomously finds pending issues and solves related problems, and in so doing, raises the social quality and establishes the conditions for health promotion. Thus, the significance of neighborhood needs to be discovered and created in a new way through the development of community capacity.