Clustering web documents based on Multiclass spectral clustering
| Autor: | Xing He, Jiabing Wang, Yi-Rong Cai, Zhong-Xian Zhang |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Clustering high-dimensional data
Brown clustering Fuzzy clustering Information retrieval Computer science Correlation clustering Conceptual clustering Image segmentation Document clustering computer.software_genre Spectral clustering Multiclass classification Statistical classification ComputingMethodologies_PATTERNRECOGNITION Data stream clustering CURE data clustering algorithm Consensus clustering Canopy clustering algorithm FLAME clustering Data mining Cluster analysis computer |
| Zdroj: | ICMLC |
| DOI: | 10.1109/icmlc.2011.6017004 |
| Popis: | Multiclass spectral clustering is a clustering method which has been successfully applied in image segmentation and many other aspects. In this paper, Multiclass spectral clustering is used to cluster web documents including both English and Chinese pages. Through experiments, we found that Multiclass spectral clustering can be well used in web document clustering, and the method not only works well to cluster English web documents but also works well to cluster Chinese web documents clustering. We applied our method to a web search engine, and users can get the suitable results easily by just selecting the desirable classes. |
| Databáze: | OpenAIRE |
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