ML Anthology

Semi-Supervised Document Clustering with Simultaneous Text Representation and Categorization

Yanhua Chen, Lijun Wang, Ming Dong
ECML-PKDD 2009 pp. 211-226
doi:10.1007/978-3-642-04180-8_31 /ecmlpkdd/2009/chen2009ecmlpkdd-semisupervised/

Abstract

In order to derive high quality information from text, the field of text mining has advanced swiftly from simple document clustering to co-clustering with words and categories. However, document co-clustering without any prior knowledge or background information is a challenging problem. In this paper, we propose a Semi-Supervised Non-negative Matrix Factorization (SS-NMF) framework for document co-clustering. Our method computes new word-document and document-category matrices by incorporating user provided constraints through simultaneous distance metric learning and modality selection. Using an iterative algorithm, we perform tri-factorization of the new matrices to infer the document, category and word clusters. Theoretically, we show the convergence and correctness of SS-NMF co-clustering and the advantages of SS-NMF co-clustering over existing approaches. Through extensive experiments conducted on publicly available data sets, we demonstrate the superior performance of SS-NMF for document co-clustering.

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Cite

Text

Chen et al. "Semi-Supervised Document Clustering with Simultaneous Text Representation and Categorization." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009. doi:10.1007/978-3-642-04180-8_31

Markdown

[Chen et al. "Semi-Supervised Document Clustering with Simultaneous Text Representation and Categorization." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009.](https://mlanthology.org/ecmlpkdd/2009/chen2009ecmlpkdd-semisupervised/) doi:10.1007/978-3-642-04180-8_31

BibTeX

@inproceedings{chen2009ecmlpkdd-semisupervised,
  title     = {{Semi-Supervised Document Clustering with Simultaneous Text Representation and Categorization}},
  author    = {Chen, Yanhua and Wang, Lijun and Dong, Ming},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2009},
  pages     = {211-226},
  doi       = {10.1007/978-3-642-04180-8_31},
  url       = {https://mlanthology.org/ecmlpkdd/2009/chen2009ecmlpkdd-semisupervised/}
}