智慧型手機是近年來成長相當快速的產業，然而受限於價格因素，行動上網用戶確未有同步的成長。舉例而言，台灣區行動上網用戶不及行動通訊總用戶的50%。價格的因素同樣地也對加值服務 (VAS) 造成影響，約75% 的用戶會首先考慮價格才會去選擇感興趣的加值服務。調降行動上網及加值服務費率勢必增加其用戶數，使商業規模與效益更為顯著。因此我們提出一套行動廣告概念架構，主要涉及電信業者 (Telecommunication Carriers)、廣告商 (Advertiser) 及行動用戶 (Subscriber)，使得三方均獲利的局面。電信業者做為廣告平台提供者，藉此架構能招攬更多廣告商；廣告商利用此平台向電信業者註冊欲促銷的廣告，並且支付一筆合理的刊登費用(電信業者獲利)；用戶為了得到行動上網費率的補償(用戶獲利)，願意訂閱由電信業者發送的促銷廣告至行動裝置。此系統不僅為電信業者帶來更多行動通訊的客戶，還會有額外廣告收入。本廣告代理平台，對電信業者、廣告商、與行動用戶都具有極大的商業誘因與利益，相信在此架構下，能夠創造三贏的局面。
不過如何將適合的廣告在對的時間、對的地點發送給對的使用者是非常關鍵的議題。我們歸納三個主要的關鍵議題： (1)何時呈現廣告能夠確保使用者注意廣告，且避免多餘廣告發送? (2)以何種形式呈現廣告? (3)針對不同使用者呈現何種廣告? 關於第一個和第二個議題，在設計上，一方面必須確保使用者能看到廣告，另一方面也要不過份叨擾使用者使用手機。一種做法是以特定應用程式如手機瀏覽器做為內嵌廣告的介面，讓使用者在使用應用程式的同時也看到廣告。然而缺點在於使用者也可能完全忽略廣告而專注於應用程式的使用；另一方面只允許單一應用程式可以使用無線網路，在設計也有比較大的難處。這也是行動廣告研究所要克服的困難。關於第三個議題，要配置合適的廣告，除了考慮廣告內容和使用者興趣匹配程度，以及合作式過濾法推薦廣告方式外，在手機上我們還可以考量廣告所屬地理位置和使用者所在位置的可達性，因此有關使用者的速度、交通模式等都是可以幫助廣告配置的因素。

Mobile devices (e.g. smart phone, PDAs, vehicle phone, and e-books) are becoming more and more popular. However, mobile broadband subscriptions are only about 20 percent of the mobile subscriptions. Part of the reasons is due to the high payments requirement for broadband subscriptions. On the other hand, US mobile ad spend will exceed US$1 billion in 2011 according to emarketer.com. Therefore, the idea of this paper is to increase broadband subscribers by providing free or discounted fees through the deployment of mobile advertising framework by the telecommunication system. In this framework, telecommunication carriers run the ads agent platform to attract investments from advertisers. Subscribers read promotional advertisements that are sent to subscribers’ mobile phones to get discounted payment of mobile Internet accessing from telecommunication carriers. While the advertisers pay a reasonable price for advertising, the possible commercial activities will bring revenues to advertisers. As a result, this framework is a triple-win for telecommunication carriers, advertisers and subscribers.
In this paper, we describe a framework for delivering appropriate ads of the ideal time at the ideal place to the ideal subscriber is the three key issues on how to show the ads, when to show the ads, and what potential ads to be clicked by the subscribers. Based on our research in the past two years on contextual advertising, we hope to take user velocity and user location into consideration.

[1] Anagnostopoulous, A., Broder, A.Z., Gabrilovich, E., Josifovski, V., & Riedei, L. (2007). Just-in-Time Contexual Advertising. In Proceedings of the 16th International Conference on Conference on Information and Knowledge Management (ACM CIKM’07) (pp. 331-340). Lisbon: ACM.
http://portal.acm.org/citation.cfm?id=1150411
[2] Broder, A., Fontoura, M., Josifovski, V., & Riedel, L. (2007). A semantic approach to contextual advertising. In Proceedings of the 30th International conference on Research and Development in Information Retrieval (ACM SIGIR’07) (pp. 559-566). Amsterdam: ACM.
[3] Chatterjee, P., Hoffman, D. L., and Novak, T. P., “Modeling the Clickstream: Implications for Web-Based Advertising Efforts,” Marketing Science, vol. 22, pp. 520-541, 2003.
[4] Chen, P.-T., Hsieh, H.-P., Cheng, J. Z., Lin, Y.-S. (2009) Broadband Mobile Advertisement: What are the Right Ingredient and Attributes for Mobile Subscribers, PICMET.
[5] ChoiceStream. (2005). ChoiceStream personalization survey: consumer trends and perceptions, http://www.choicestream.com/pdf/ChoiceStream_PersonalizationSurveyResults2005.pdf.
[6] East, R., Consumer Behaviour, Prentice Hall, 1997.
[7] Fan, T.-K., & Chang, C.-H. (2009). Sentiment-Oriented Contextual Advertising. The 31st European Conference on Information Retrieval (ECIR’09), LNCS, 5478, 202-215.
[8] Fan, T.-K. and Chang, C.-H (2011).: Blogger-Centric Contextual Advertising. Journal of Expert Systems With Applications, Vol. 38, Issue. 3, pp. 1777-1788.
[9] Fan, T.-K. and Chang, C.-H (2010).: Sentiment Oriented Contextual Advertising. Journal of Knowledge and Information System, Vol. 23, No. 3, pp. 321-344.
[10] Feng, J., Bhargava, H.K., & Pennock, D. (2003). Comparison of Allocation Rules for Paid Placement Advertising in Search Engine. In Proceedings of the 5th International conference on Electronic Commerce (ACM EC’03) (pp. 294 - 299). Pittsburgh: ACM.
[11] Giuffrida G., Sismeiro C.., Tribulato G. (2008). Automatic content targeting on mobile phones, EDBT’07.
[12] I. S. D., S. M., and D. S. M.. “Information-theoretic co-clustering.” (2003) In Proceedings of the ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (KDD ’03) (pp. 89-98), New York.
[13] Kazienko, P., & Adamski, M. (2007). AdROSA-Adaptive personalization of web advertising. Information Sciences, 177(11), 2269-2295.
[14] Lacerda, A., Cristo, M., Goncalves, M.A., Fan, W.g., Ziviani, N., & Ribeiro-Neto, B. (2006). Learning to advertise. In Proceedings of the 29th International Conference on Research and Development in Information Retrieval (ACM SIGIR’06) (pp. 549-556) Seattle: ACM.
[15] Langheinrich, M., Nakamura, A., Abe, N., Kamba, T., & Koseki, Y. (1999). Unintrusive customization techniques for Web advertising. The International Journal of Computer and Telecommunications Networking, 31(11-16), 1259-1272.
[16] Novak, T. P. and Hoffman, D. L. (1997) New metrics for new media: toward the development of Web measurement standards. World Wide Web Journal 2, 213-246, 1997.
[17] Parsons, J., Gallagher, K., & Foster, K.D. (2000). In Messages in the Medium: An Experimental Investigation of Web Advertising Effectiveness and Attitudes toward Web Content. In Proceeding of the 33rd Annual Hawaii International Conference on System Sciences (HICSS’00). Hawaii: IEEE.
[18] Penev, A., Wong, R. K. (2009) Framework for Timely and Accurate Ads on Mobile Devices, CIKM, November 2–6, 2009, Hong Kong.
[19] Rao, B., Minakakis, L. (2003) "Evolution of Mobile Location-based Services," COMMUNICATIONS OF THE ACM.
[20] Ribeiro-Neto, B., Cristo, M., Golgher, P.B., & Moura, E.S.d. (2005). Impedance coupling in content-targeted advertising. In Proceedings of the 28th annual international Conference on Research and Development in Information Retrieval (ACM SIGIR’05) (pp. 496-503). Salvador: ACM.
[21] Turban, E., Lee, N., King, D., Chung, H.M., Electronic Commerce—A Managerial Perspective, Prentice Hall, 2000.
[22] Varshney, U., Vetter, R. (2002). Mobile Commerce: Framework, Applications and Networking Support," Mobile Networks and Applications.
[23] Wang, C., Zhang, P., Choi, R., & D''Eredita, M. (2002). Understanding consumers attitude toward advertising. In Eighth Americas Conference on Information Systems (pp. 1143-1148).
[24] Xu, D. J., Liao, S. S., Li, Q. (2008). Combining empirical experimentation and modeling techniques: A design research approach for personalized mobile advertising applications, Decision Support Systems 44.
[25] Zhang, Y., Surendran, A.C., Platt, J.C., & Narasimhan, M. (2008). Learning from multi-topic web documents for contextual advertisement. In Proceeding of the 14th International conference on Knowledge Discovery and Data mining (ACM SIGKDD’08) (pp. 1051-1059). Las Vegas: ACM.