Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

7

FLAIRS
2001

favoriteEmaildiscussreport

109views Artificial Intelligence» more FLAIRS 2001»

A Lattice-Based Approach to Hierarchical Clustering

13 years 5 months ago

A Lattice-Based Approach to Hierarchical Clustering

Download www.aaai.org

The paper presents an approach to hierarchical clustering based on the use of a least general generalization (lgg) operator to induce a lattice structure of clusters and a category utility objective function to evaluate the clustering quality. Theobjective function is integrated with a lattice-based distance measureinto a bottom-up control strategy for clustering. Experimentswith well-knowndatasets are discussed.

Zdravko Markov

Real-time Traffic

Artificial Intelligence | Clustering Quality | FLAIRS 2001 | Hierarchical Clustering | Utility Objective Function |

claim paper

Related Content

» Hierarchical Representatives Clustering with Hybrid Approach

» A Coherent and Heterogeneous Approach to Clustering

» Hierarchical Ensemble Clustering

» Decision treebased context clustering based on cross validation and hierarchical priors

» Markerbased Hierarchical Segmentation and classification approach for hyperspectral imager...

» Combining hierarchical clusterings using mintransitive closure

» Shared farthest neighbor approach to clustering of high dimensionality low cardinality dat...

» Multilingual Evidence Improves Clusteringbased Taxonomy Extraction

» Improving Speaker Diarization by Cross EM Refinement

Post Info
More Details (n/a)

Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2001
Where	FLAIRS
Authors	Zdravko Markov

Comments (0)