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: linear programming
Mining scientific results through the combined use of clustering and linear programming techniques
A. Tagarelli, I. Trubitsyna, S. Greco. Mining scientific results through the combined use of clustering and linear programming techniques. 6th International Conference on Enterprise Information Systems (ICEIS ’04), vol. 2, pp. 84-91. Porto, Portugal, April 14-17, 2004.
Posted in Conference Proceedings
Tagged clustering, Data envelopment analysis, linear programming
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Combining Linear Programming and Clustering Techniques for the Classification of Research Centers
A. Tagarelli, I. Trubitsyna, S. Greco. Combining Linear Programming and Clustering Techniques for the Classification of Research Centers. The European Journal on Artificial Intelligence, AI Communications 17(3):111-122, 2004.
Mining Scientific Results to Measure the Efficiency of Research Centers
A. Tagarelli, I. Trubitsyna, A. Mecchia, T. Mostardi, R. Pupo. Mining Scientific Results to Measure the Efficiency of Research Centers. 11th Italian Symposium on Advanced Database Systems (SEBD ’03), pp. 147-160. Cetraro, Italy, June 2003.