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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Meng-Lun Wu Chia-Hui Chang Rui-Zhe Liu Teng-Kai Fan |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Computer Science Information Engineering, National Central University Jhongli, Taoyuan (Meng-Lun Wu; Chia-Hui Chang; Rui-Zhe Liu; Teng-Kai Fan) |
| Abstract | Clustering plays an important role in data mining, as it is used by many applications as a preprocessing step for data analysis. Traditional clustering focuses on grouping similar objects, while two-way co-clustering can group dyadic data (objects as well as their attributes) simultaneously. In this research, we apply two-way co-clustering to the analysis of online advertising where both ads and users need to be clustered. The key data that connect ads and users are contained in the user-ad link matrix, which denotes the ads that a user has linked. We proposed a three-staged clustering that makes use of the three data matrices to enhance clustering performance. In addition, an iterative cross co-clustering algorithm is also proposed for two-way co-clustering. The experiment is performed using the advertisement and user data from Morgenstern, a financial social website that focuses on the agent of advertisements. The result shows that three staged clustering provides better performance than traditional clustering, while iterative co-clustering completes the task more efficiently. |
| Starting Page | 587 |
| Ending Page | 593 |
| File Size | 293701 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424476398 |
| e-ISBN | 9781424476404 |
| DOI | 10.1109/COMPSYM.2010.5685445 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-16 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Clustering evaluation Clustering algorithms KL divergence Dyadic data analysis Classification algorithms Matrix decomposition Decision trees Advertising Decision tree Equations Co-clustering |
| Content Type | Text |
| Resource Type | Article |
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