Constructing Tagging-based Mobile Ad Profiling: An Incremental 3-layer Clustering Framework
Date Issued
2013
Date
2013
Author(s)
Lin, Yi-Ling
Abstract
Smart phones have become very ubiquitous in recent years, and in-app advertising is a primary business model for mobile applications. Following this trend, researchers are interested in how to provide appropriate ads to target users. In this thesis, we particularly focus on considering and analyzing the role of apps in ad-clicking behavior. We believe that user preference will be directly reflected on the apps they use. To capture the hidden interests of their target customers, advertisers should identify the characteristics of apps. On the other hand, adaptive profiling has been proposed to match user profiles and campaign profiles. However, when applying this concept to mobile advertising, how to produce profiles from tremendous amounts of daily mobile data is a challenging issue. We explore the problem of producing mobile ad profiles from mobile user-generated data and incorporate the usage log of apps into ad profiling. We propose a novel 3-layer clustering framework to realize the tagging-based mobile ad profiling. Moreover, since new usage logs will be generated continually, an incremental mechanism is also designed to address the update issue and provide up-to-date clustering results.
Subjects
手機廣告
廣告剖析
分群演算法
漸進式更新
使用者行為定位
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-102-R00921042-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):24c7826a86b99b7248895b63c572eba5