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題名 | 基於情境感知的個人化中文廣告推薦 |
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作者姓名(中文) | 陳榮昌; 蕭朝維; | 書刊名 | 資訊科技國際期刊 |
卷期 | 7:1 2013.06[民102.06] |
頁次 | 頁2-18 |
分類號 | 497.468 |
關鍵詞 | 個人化廣告推薦; 點閱率; 情境感知; 情境資訊; 模糊推論引擎; Personal advertisement recommendation; Click through rates; Context-awareness; Contextual information; Fuzzy inference engine; |
語文 | 中文(Chinese) |
中文摘要 | 現今的網路廣告普遍還是以隨機的方式 來推薦廣告,使用者對所推薦的廣告不一定感 興趣,使得廣告點閱率偏低。目前也有針對個 人化廣告推薦的研究,但卻沒有針對中文廣告 的推薦。因此,本研究希望發展一個可以針對 中文廣告的個人化推薦系統。我們將以情境感 知的架構為基礎,從分析使用者的交談内容及 其個人資訊中來蒐集短期和長期的情境資 訊,並且利用這些情境資訊經由模糊推論引擎 找出符合使用者需求的廣告,藉此找出使用者 感興趣的廣告。經由本研究的實驗結果顯示, 本研究所提出的個人化廣告推薦確實能夠改 善傳統廣告的點閱率,如此將可讓廣告商獲得 良好的廣告效益,也能讓使用者取得感興趣的廣告。 |
英文摘要 | Nowadays, the advertisings are often recommended by random selection. These recommended advertisings may not be interested by users. Thus, the click through rate(CTR) may be decreased. There are many studies about personal advertisement recommendation in these years. But, we can not find the efforts about the recommendation of Chinese advertisement. Hence, we propose a personal advertising recommendation system for Chinese advertisings. We employ the context-awareness technology to gather both short-term contextual information and long-term contextual information from the dialogue of users. And then, analyzing these contextual information by fuzzy inference engine to find the advertising what the user wants. Finally, by experiment results,we prove that our proposed method really improve the click through rates(CTR). Therefore, through our approach, the advertisers can acquire more effective advertising and the user can also acquire his interested advertisements. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。