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    题名: A recommendation mechanism for contextualized mobile advertising
    作者: 苑守慈
    Yuan,Soe-Tysr;Tsao,Y.W.
    关键词: Mobile commerce;Mobile advertising;Neural Network;Sensitivity;Analysis;Information filtering;Recommender systems
    日期: 2003-05
    上传时间: 2009-01-17 16:36:04 (UTC+8)
    摘要: Mobile advertising complements the Internet and interactive television advertising and makes it possible for advertisers to create tailor-made campaigns targeting users according to where they are, their needs of the moment and the devices they are using (i.e. contextualized mobile advertising). Therefore, it is necessary that a fully personalized mobile advertising infrastructure be made. In this paper, we present such a personalized contextualized mobile advertising infrastructure for the advertisement of commercial/non-commercial activities. We name this infrastructure MALCR, in which the primary ingredient is a recommendation mechanism that is supported by the following concepts: (1) minimize users` inputs (a typical interaction metaphor for mobile devices) for implicit browsing behaviors to be best utilized; (2) implicit browsing behaviors are then analyzed with a view to understanding the users` interests in the values of features of advertisements; (3) having understood the users` interests, Mobile Ads relevant to a designated location are subsequently scored and ranked; (4) Top-N scored advertisements are recommended. The recommendation mechanism is novel in its combination of two-level Neural Network learning, Neural Network sensitivity analysis, and attribute-based filtering. This recommendation mechanism is also justified (by thorough evaluations) to show its ability in furnishing effective personalized contextualized mobile advertising.
    關聯: Expert Systems with Applicationa, 24(4), 399-414
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1016/S0957-4174(02)00189-6
    DOI: 10.1016/S0957-4174(02)00189-6
    显示于类别:[資訊管理學系] 期刊論文

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