基於情境感知與社群推薦的行動廣告機制

Abstract

隨著智慧型手機和平板電腦等智慧型行動裝置普及和流行,他們已經成為我們生活中不可或缺的部份。行動廣告逐漸為廠商和廣告商帶來巨大的商機。許多成功的公司，像蘋果公司和谷歌公司都開始在其服務中設計行動廣告推薦的機制以獲取利潤。然而行動廣告也面臨著巨大的挑戰，的在動態的行動環境中，用戶需求變化較快，而現有的廣告推薦機制又不能夠精確定位用戶需求，造成了現在行動廣告有效性和效益偏低，從一些指標中我們瞭解到，現在行動廣告每千次展示成本（eCPM）的有效性過低，而且其平均每月每用戶收入(ARPU)也非常低。所以在本次研究中，爲了解決以上的問題，我們提出來一種基於情境資訊和社群行為參考的的行動廣告推薦機制。在該機制中，我們採用了情境感知技術和社群行為參考的概念，以提高行動廣告的效率和效益。通過我們的系統，我們試圖通過在不斷變化的環境中為用戶找到最合適的廣告，並且希望通過朋友的影響來有效提高用戶對於廣告的接受度。

Mobile devices, such as smartphones and Tablets, have been so popular that they are to be indispensable to daily life, which brings a bright future for mobile advertising. Many great companies have adopted mobile advertising in their services, such as Apple and Google. But the low effective cost per thousand impressions (eCPMs) and the low the average revenue per user (ARPU), caused by inaccurate targeting in dynamic environment and advertising avoidance, are big challenges facing with the mobile advertisers now. In this paper, we propose a novel mobile advertising recommender system by incorporating the concepts of “context-fitness” and “social referral”. By using our system, we could identify most suitable ads for targeted users in the changing environment and improve the ads effectiveness by taking friends’ influence into consideration.