Title :
Personalized Advertising Strategy for Integrated Social Networking Websites
Author :
Hsieh, Chang-Tai ; Liang, Chun-Ming ; Chou, Shih-Chun
Author_Institution :
Inst. for Inf. Ind. (III), Taipei
Abstract :
In addition to provide major funding for many Internet companies, online advertising creates a disutility to consumers, subsequently reducing market share. However, previous works focus only on the topical relevance of ads and, in doing so, neglect consumer attitudes. From the view of text processing, they focus only on the topic dimension of texts, while paying no attention to the sentiment dimension. This work proposes a feature extraction process to match advertisement and targeted users by extracting features from the userpsilas profile and advertisement specification. First, the proposed platform relies on mine characteristics supplied by a user to his avatar including preferred color, style and feeling. Second, the system selects the best matching advertisement based on the userpsilas variable interests (as expressed on his blog). These features are scored and finally these advertisements are conveyed to the target users by product. Experimental results in several topics demonstrate that the proposed framework works well in detecting a userpsilas potential preferences, and in recommending suitable advertisements.
Keywords :
advertising data processing; avatars; feature extraction; social networking (online); advertisement specification; avatar; feature extraction; matching advertisement; online advertising; personalized advertising; social networking Web site; user potential preference; user profile; Social network; advertisment strategy; user preference mining;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
DOI :
10.1109/WIIAT.2008.156