News & Highlights
- Co-organized Workshop: MultiClust Workshop at ACM SIGKDD 2013
- Minimizing the variance of cluster mixture models for clustering uncertain objects
- A Segment-based Approach To Clustering Multi-Topic Documents
- Exploring Dictionary-based Semantic Relatedness in Labeled Tree Data
- Projective Clustering Ensembles
- Uncertain Centroid based Partitional Clustering of Uncertain Data
- XML Document Clustering Using Structure-Preserving Flat Representation of XML Content and Structure
- Co-organized Workshop: 3Clust Workshop at PAKDD 2012
- A Statistical Model for Topically Segmented Documents
- SIGIR Report on INEX 2010
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classification clustering clustering ensembles document clustering DSA email mining fuzzy logics information extraction linear programming mass spectrometry optimization PDF documents projective clustering semantic relatedness similarity detection time series uncertain data web content mining web personalization web usage mining web wrapping WordNet word sense disambiguation wrapping XML XML content clustering XML mining XML structure clustering
Tag Archives: uncertain data
Minimizing the variance of cluster mixture models for clustering uncertain objects
F. Gullo, G. Ponti, A. Tagarelli. Minimizing the variance of cluster mixture models for clustering uncertain objects. Statistical Analysis and Data Mining (SAM) 6(2):116-135, 2013. Online First: November 19, 2012.
Posted in Journals, News
Tagged clustering, uncertain cluster prototype, uncertain data
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Uncertain Centroid based Partitional Clustering of Uncertain Data
F. Gullo, A. Tagarelli. Uncertain Centroid based Partitional Clustering of Uncertain Data. Proceedings of the VLDB Endowment (ACM), 5(7):610-621, 2012. PDF
Minimizing the Variance of Cluster Mixture Models for Clustering Uncertain Objects
F. Gullo, G. Ponti, A. Tagarelli. Minimizing the Variance of Cluster Mixture Models for Clustering Uncertain Objects. 10th IEEE International Conference on Data Mining (ICDM ’10), pp. 839-844. Sydney, Australia, December 14-17, 2010.
Posted in Conference Proceedings
Tagged clustering, uncertain data, variance of mixture models
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Hierarchical Clustering of Microarray Data with Probe-level Uncertainty
F. Gullo, G. Ponti, A. Tagarelli, G. Tradigo, P. Veltri. Hierarchical Clustering of Microarray Data with Probe-level Uncertainty. 22nd IEEE International Symposium on Computer-Based Medical Systems (CBMS ’09). Albuquerque, New Mexico, USA, August 3-4, 2009. PDF
Information-Theoretic Hierarchical Clustering of Uncertain Data
F. Gullo, G. Ponti, A. Tagarelli, S. Greco. Information-Theoretic Hierarchical Clustering of Uncertain Data. 17th Italian Symposium on Advanced Database Systems (SEBD ’09), pp. 273-280. Camogli (Genova), Italy, June 21-24, 2009.
A Hierarchical Algorithm for Clustering Uncertain Data via an Information-Theoretic Approach
F. Gullo, G. Ponti, A. Tagarelli, S. Greco. A Hierarchical Algorithm for Clustering Uncertain Data via an Information-Theoretic Approach. 8th IEEE International Conference on Data Mining (ICDM ’08), pp. 821-826. Pisa, Italy, December 15-19, 2008.
Clustering Uncertain Data Via K-Medoids
F. Gullo, G. Ponti, A. Tagarelli. Clustering Uncertain Data Via K-Medoids. 2nd International Conference on Scalable Uncertainty Management (SUM ’08), pp. 229-242, LNAI 5291. Naples, Italy, October 1-3, 2008.