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조상철 관광경영학회 2000 관광경영연구 Vol.8 No.-
The purpose of this study is to examine the features of situational influence in the hotel restaurant Choice and to help the managers of Hotel restaurant in marketing, management and sales promotion in such a competitive situation of the hotel industry. More specifically, it has investigated the differences between the restaurant choice and choice factors in situational influence and identified there are also differences between hotel choices and choice factors in situational influence and demographic variables. This study should be considered more since the sample was not completely random and need to deveiop the dimension on situational influence factors. Therefore, the more systematic and continuous study should be executed to overcome those kind of limits.
池元哲,趙相喆 弘益大學校 科學技術硏究所 2001 科學技術硏究論文集 Vol.12 No.-
Association Rule Mining,(Agrawal et al., 1993) is an exploration method which searches associative relations between item sets in large database. Association Rule Mining, in general, searches association between qualitative items. To adapt Association Rule Mining to quantitative attributes, Quantitative Association Rule Mining is introduced in 1996. Sequential Pattern Mining and N-Dimensional Inter Transaction Mining are applications of Association Rule for Time series analysis by extending time dimensions to the Association Rule. Analyzing complex time series, such as stock price movement, using quantitative model is limited, and Technical Analysis like a chart analysis is an alternative approach for them. Technical Analysis recognizes patterns, and analyzes impacts effected by the pattern. In this work, we defined pattern on the time series syntactically and analyzed the patterns and recognized the patterns which is frequently emerges in the time series, and, explored the other patterns as an impact of discovered patterns in former step. For this purpose, we used N-dimensional Inter Transaction Association Rule and syntactically described pattern(of both quantitative, qualitative attribute). So it enables pattern recognition, analyzing impacts and forecasting of complex time series such as stock prive movement