Ensemble subspace clustering of text data using two-level features
文献类型：期刊论文
| 作者 | He Zhao; Salman Salloum; Yeshou Cai; Joshua Zhexue Huang |
| 刊名 | INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
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| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | This paper proposes a new integrated method for ensemble subspace clustering of high dimensional sparse text data. Our method employs two-level feature representation of text data (words and topics) to generate clusters from subspaces. We also use ensemble clustering to increase the robustness of the clusters. This method depends on topic modeling to get the two-level feature representation of text data and to generate different ensemble components. By using both topics and words to cluster text data, we can get more interpretable clusters as we can measure the weight of words and topics in each cluster. In order to evaluate the proposed method, we have conducted several experiments on seven real-life data sets. While some of these data sets are easy to cluster, others are hard, and some others contain unbalanced data. Experimental results on this diversity of data sets show that our method outperforms other methods for ensemble clustering. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/12568]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS |
| 推荐引用方式 GB/T 7714 | He Zhao,Salman Salloum,Yeshou Cai,et al. Ensemble subspace clustering of text data using two-level features[J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS,2017. |
| APA | He Zhao,Salman Salloum,Yeshou Cai,&Joshua Zhexue Huang.(2017).Ensemble subspace clustering of text data using two-level features.INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. |
| MLA | He Zhao,et al."Ensemble subspace clustering of text data using two-level features".INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
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