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WISE
2002
Springer

A Unified Framework for Clustering Heterogeneous Web Objects

8 years 10 months ago
A Unified Framework for Clustering Heterogeneous Web Objects
In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a unified feature space, their flexibilities to explore and adjust contributing effect from different heterogeneous information are compromised. In contrast, our framework enables separate clustering of homogeneous data in the entire process based on their respective features, and a layered structure with link information is used to iteratively project and propagate the clustered results between layers until it converges. Our experimental results show that such a scheme not only effectively overcomes the problem of data sparseness caused by the high dimensional link space but also improves the clustering accuracy significantly. We achieve 19% and 41% performance increases when clustering web-pages and users based on a semi-synthetic web log. Finally, we show a real clustering result based on UC Berkeley's we...
Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma
Added 16 Jul 2010
Updated 16 Jul 2010
Type Conference
Year 2002
Where WISE
Authors Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma
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