Data Mining Techniques with Data Imputation in Analyzing The Re-accommodation Willness of Visitors

• Main Authors: Yang, Shenghsun, 楊昇勳
• Other Authors: Pai, PingFeng
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/18354073339619778521

碩士 === 國立暨南國際大學 === 資訊管理學系 === 100 === With the socio-economic growth in recent years, the people of Taiwan go out to the number of tourists become more, the formation of the national tourism culture. Along with the prevalence of domestic public leisure and tourism, and tourism characteristics relative to the multiple changes and promote the vigorous development of the Bed and Break market. B & B fast gathering place is located in the popular tourist attractions and accommodation visitors were an important factor to promote local attractions industry. Guests as demand for information generated, guesthouse owners recognize the individual a guesthouse owners can master the guests as information is limited. It’s easier on the human decision-making confusion. This study will take advantage of the approach of missing values, missing values information to improve the questionnaires. For B & B product image, brand personality and repurchase intention, and the combination of feature extraction techniques to compare. First, the missing values handling methods, such as delete method and multiple imputation method for missing values and then the individual is added to the differential algorithm, feature extraction, and data characteristics to elect key features. Secondary, compared the feature extraction from the differential evolution. Finally, in the accuracy of the C4.5 decision tree and the tree structure rules. In order to establish a passenger re-accommodation rule base, so the guesthouse owners to meet the needs of guests as again stay will be able basis.