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研究生(外文):Yi-Cih Chen
論文名稱(外文):On improving the effectiveness of Mobile Advertising
指導教授(外文):Seng-Cho T. Chou
口試委員(外文):Hsin-Min LuWen-Kuo Chen
外文關鍵詞:mobile advertisingclusteringuser behaviorclick through rate
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With the ever-increasing number of smart phones, mobile is growing faster than all other digital advertising formats, as advertisers begin allocating dollars to catch the eyes of a growing class of "mobile-first" users. There is a fertile market for personalized adverting. So, the challenge is how to get your users to click more often on the ads appearing on your mobile property. More users clicking on the ads would primarily mean advertising money for the company.

Hence, we collected datas from a company who has its mobile applications and makes effort to enhane their mobile Ad effectiveness. Then we used the clustering techniques and decision tree model to find out what factors are related to the click through rate (CTR). Finally, we found that both Ad itself and user behavior influence the Ad effectiveness. For Ad itself, different types of Ads such as Ad categories cause different CTR. For user behavior, there are many factors that should be considered also, for instance, their drama preference, watching hours preference and so on would cause different CTR too. In conclusion, knowing the key factors and using the prediction model can help company to enhance their Ad effectiveness.

第一章 緒論 1
第一節 研究背景與動機 2
第二節 研究問題 3
第三節 研究流程 3

第二章 文獻探討 5
第一節 行動廣告 5
壹 行動廣告 5
貳 行動行銷 5
參 行動廣告類型 6
肆 行動應用程式廣告類型 7
第二節行動廣告效果 9
壹 衡量行動廣告成效 / 行動廣告有效性 9
貳 影響行動廣告成效的因素 10

第三章 研究方法 14
第一節 研究架構 14
第二節 資料搜集方法 15
壹 資料來源 15
貳 資料合併與整理方式 18
第三節 研究流程 19
第四節 資料分析方法 20
壹 敘述性統計分析 20
貳 主成分分析 20
參 群集分析 20
肆 屬性選擇 21
陸 決策樹分析 22
第四章 資料分析結果 24
第一節 統計分析結果 25
壹 主成分分析 25
貳 集群分析 26
參 定量分析驗證分析 27
第二節 決策樹分析 42
壹 屬性選取 42
貳 決策樹分析 44

第五章 結論與建議 52
第一節 結論 52
第二節 建議 53

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