http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
신택수,장근녕,박유진 한국지능정보시스템학회 2006 지능정보연구 Vol.12 No.4
This study proposed a customer preference estimation model for production recommendation and a method to enhance the performance of product recommendation using the estimated customer preference information. That is, we suggested customer preference estimation model to estimate exactly customer’s product preference with his behavior. This model shows the relationship of customer’s behaviors with his preferences. The proposed estimation model is optimized by learning the relative weights of customer’s behavior variables to have an effect on his preference and enables to estimate exactly his preference. To validate our proposed models, we collected virtual book store data and then made a comparative analysis of our proposed models and a benchmark model in terms of performance results of collaborative filtering for product recommendation. The benchmark model means a prior preference weighting model. The results of our empirical analysis showed that our proposed model performed better results than the benchmark model. 본 연구는 상품추천을 위해 필요한 고객 선호도 추정모형(Customer Preference Estimation Model)을 제안하고, 이러한 선호도 추정결과에 따른 선호도 정보를 이용하여 궁극적으로 상품추천의 성과를 제고시키기 위한 방법을 제시하였다. 즉, 제품에 대한 고객 선호 영향요인들과 고객 선호도와의 관계를 모형화 함으로써 고객 선호도를 보다 더 정확히 추정할 수 있는 새로운 선호도 추정모형을 제안하였다. 이 제안모형은 선호도 영향요인들의 상대적인 가중치를 선호도 최적화 학습을 통해 도출함으로써, 보다 정확한 선호도 측정을 가능하게 해 준다. 한편, 이 모형의 타당성을 검증하기 위해서 본 연구에서는 가상서점 고객들을 대상으로 고객 선호도 정보를 수집한 후, 본 제안모형을 적용했을 때의 협업 필터링의 추천성과와 사전가중치 부여방식인 기존 선호도 계산식을 이용했을 경우의 추천성과를 비교 분석하였다. 이에 대한 실증분석 결과는 본 연구에서 제안한 선호도 추정모형을 적용했을 때의 협업 필터링의 성과가 기존 선호도 계산방식을 적용했을 때의 협업 필터링의 성과보다 더 우수한 것으로 나타났다.
학술세션Ⅲ : 지식경영과 창의성 ; 중국현지기업의 사회자본이 지적자본과 기업의 혁신활동에 미치는 영향
신택수,최종군 한국지식경영학회 2014 지식경영 학술심포지움 Vol.2014 No.-
Social capital of the organizational dimension is recognized as the origin of the knowledge capital creation, and it becomes the mechanisms which explains the interaction of members or which accelerates the behavior of the members to attain the goal of an organization (Park 2001; Jang et al. 2011). Lots of researches show that this kind of relation empirically exists. Social capital and knowledge capital of an organization are one of the most important competitive advantages that a company needs the most. They are also the main dynamic drivers of the innovation activity. This study deeply analyzes that relation and examine the impact and role of an organization``s social capital and intellectual capital on innovation activities in an organization. In other words, the purpose of the study is to analyze the impact of social capital on the intellectual capital and innovation activities of the China local companies. This study empirically analyzed the survey data collected from the employees of the companies located in China. Our empirical results of this study showed that social capital has significantly causal effects on the relationship between social capital and intellectual capital partially and also showed the intellectual capital has significantly positive effects on the innovation activities partially.
무선 LAN에서 Ad-Hoc과 Infrastructure 모드의 자동전환 기술 설계 및 구현
신택수,조성민,민상원,Shin Taek-Su,Jo Sung-Min,Min Sang-Won 한국통신학회 2006 韓國通信學會論文誌 Vol.31 No.9A
In this paper, we propose an automatic switching technology between the ad-hoc and the infrastructure modes without user intervention in the IEEE 802.11b wireless LAN. Also, we design our proposed technology and implemented on the Linux machine. For this operation, the area within an Access Point (AP) coverage is defined as a switching area, and a node without any transmission in this area is assumed to be able to relay frames between the AP and nodes in the shaded area that is outside the coverage and cannot reach the AP. By using the proposed technology, it is possible to provide the seamless Internet access service to nodes at the ad-hoc mode in the shaded area. In this paper, we explains the operation of the detection method of the switching area, presents the flowchart and implementation environment. To prove the operation of our technology, we obtain the results of captured packets transmitted between nodes and throughput results through ftp transmission experiment. Hence, we can see that our proposed scheme can be improve the wireless access service in wireless and mobile networks. 본 논문은 IEEE 802.11b-무선 LAM 환경에서 ad-hoc 방식과 infrastructure 방식 사이의 자동 모드 전환 기술을 제안하였다. 또한 관련된 기술을 Linux 환경에 맞추어 설계 및 구현을 하였다. 제안된 메커니즘은 AP (Access Point) 서비스 영역 외곽에 switching area를 정의하고 해당 영역에 머무르는 노드는 AP와 음영지역에 있는 ad-hoc 노드를 연결 가능하게 해준다. 본 기술을 활용하여 기존 IEEE 802.11b 환경에서는 서비스가 불가능한 음영지역에 있는 노드에게도 인터넷 서비스를 제공할 수 있게 한다. 성능 검증은 switching area 감지, 패킷 전달 상황 캡춰, FTP 전송을 통한 처리량 측정으로 이루어졌고 그 결과 제안된 메커니즘기 무선 LAN 서비스를 향상 시킨다는 것을 확인할 수 있었다.
환율예측을 위한 신호처리분석 및 인공신경망기법의 통합시스템 구축
신택수,한인구 한국지능정보시스템학회 1999 지능정보연구 Vol.5 No.1
Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets batter than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U.S. dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.
신택수 서울대학교 교육연구소 2012 Asia Pacific Education Review Vol.13 No.1
This study introduced various nonlinear growth models, including the quadratic conventional polynomial model, the fractional polynomial model, the Sigmoid model, the growth model with negative exponential functions, the multidimensional scaling technique, and the unstructured growth curve model. It investigated which growth models effectively describe student growth in math and reading using four-wave longitudinal achievement data. The objective of the study is to provide valuable information to researchers especially when they consider applying one of the nonlinear models to longitudinal studies. The results showed that the quadratic conventional polynomial model fit the data best. However, this model seemed to overfit the data and made statistical inference problematic concerning parameter estimates. Alternative nonlinear models with fewer parameters adequately fit the data and yielded consistent significance testing results under extreme multicollinearity. It indicates that the alternative models denoting somewhat simpler models would be selected over the conventional polynomial model with more fixed parameters. Other practical issues pertaining to these growth models are also discussed.