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HAIS
2010
Springer
13 years 8 months ago
A Hybrid Cluster-Lift Method for the Analysis of Research Activities
A hybrid of two novel methods - additive fuzzy spectral clustering and lifting method over a taxonomy - is applied to analyse the research activities of a department. To be specifi...
Boris Mirkin, Susana Nascimento, Trevor I. Fenner,...
PAKDD
2005
ACM
142views Data Mining» more  PAKDD 2005»
14 years 2 months ago
Dynamic Cluster Formation Using Level Set Methods
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
Andy M. Yip, Chris H. Q. Ding, Tony F. Chan
CIKM
2000
Springer
14 years 25 days ago
A Semi-Supervised Document Clustering Technique for Information Organization
This paper discusses a new type of semi-supervised document clustering that uses partial supervision to partition a large set of documents. Most clustering methods organizes docum...
Han-joon Kim, Sang-goo Lee
IDA
2003
Springer
14 years 1 months ago
Fuzzy Clustering Based Segmentation of Time-Series
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
János Abonyi, Balazs Feil, Sandor Z. N&eacu...
PR
2007
340views more  PR 2007»
13 years 8 months ago
Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation
— Fuzzy c-means (FCM) algorithms with spatial constraints (FCM_S) have been proven effective for image segmentation. However, they still have the following disadvantages: 1) Alth...
Weiling Cai, Songcan Chen, Daoqiang Zhang