Xin Chen

Affiliations:
  • Drexel University, College of Information Science and Technology, Philadelphia, PA, USA


According to our database1, Xin Chen authored at least 11 papers between 2008 and 2012.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2012
Exploiting the Functional and Taxonomic Structure of Genomic Data by Probabilistic Topic Modeling.
IEEE ACM Trans. Comput. Biol. Bioinform., 2012

Modeling semantic relations between visual attributes and object categories via dirichlet forest prior.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Identifying enterotype in human microbiome by decomposing probabilistic topics into components.
Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012

2011
Perspective hierarchical dirichlet process for user-tagged image modeling.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

Inferring Functional Groups from Microbial Gene Catalogue with Probabilistic Topic Models.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010
The topic-perspective model for social tagging systems.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

A probabilistic topic-connection model for automatic image annotation.
Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

Probabilistic topic modeling for genomic data interpretation.
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine, 2010

2009
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

Exploit the tripartite network of social tagging for web clustering.
Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008
A Novel Unsupervised Feature Selection Method for Bioinformatics Data Sets through Feature Clustering.
Proceedings of the 2008 IEEE International Conference on Granular Computing, 2008


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