• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Korean Home Economics Education Association
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• v.26 no.1
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• pp.101-118
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• 2014

"Career maturity" is very crucial for high school students since it has an impact on their career path and decision-making. Not only that, it is also important in self-realization and happiness as well as maximizing human resources. When it comes to understanding high school students' career path, it is necessary to know how they perceive school life since they spend most of their time in school. It's also vital to observe in the perspective of students' personal growth. This study seeks to understand the relationship between "adaptation to school life" "self-esteem" and "career maturity". To accomplish this, the 7th additional surveys conducted by Welfare Panel Study were used. The survey was conducted among 496 high school students in order to come up with descriptive statistics and correlation between "adaptation to school life" and "self-esteem" as well as the level of "career maturity". Hierarchical multiple regression analysis was used to understand the effects of "adaptation to school life" and "self-esteem" on "career maturity." The Baron and Kennny mediation analysis were used to understand the effects when the mediating role of "self-esteem" comes into the relationship between "adaptation to school life" and "career maturity". The results of the analysis are as follows: First, the average age for high school students' "career maturity" is 2.07, while it is 1.91 for "self-esteem". For "adaptation to school life," the relationship between "obedience to school regulations" and "relationship with friends" was relatively higher than the relationship between "attitude toward school life" and "interest in school life" Second, high school students' "career maturity" "adaptation to school life" and "self-esteem" were thought to be statistically meaningful since it showed that they had a positive relationship with each other. Third, "interest in school life" "attitude toward school life" and "obedience to school life" and "relationship with friends" in which all of these are the sub factors for "adaptation to school life" together with "self-esteem" had an influence on high school students' "career maturity". Lastly, the relationship between "adaptation to school life" and "career maturity" was proved to be influenced by the partial mediating role of "self-esteem". As the study seeks to find relationships and the factors that affect high school students' "career maturity" meaningful information is given out for the development and progress of educational programs for "career maturity". This was done by understanding the fundamental and systematic approach towards "career maturity" in the students' perspective.