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IJCAI
2007
15 years 5 months ago
Semantic Smoothing of Document Models for Agglomerative Clustering
In this paper, we argue that the agglomerative clustering with vector cosine similarity measure performs poorly due to two reasons. First, the nearest neighbors of a document belo...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu
ICPR
2010
IEEE
15 years 4 months ago
Clustering Face Carvings: Exploring the Devatas of Angkor Wat
Abstract—We propose a framework for clustering and visualization of images of face carvings at archaeological sites. The pairwise similarities among face carvings are computed by...
Brendan Klare, Pavan Kumar Mallapragada, Anil K. J...
INFOCOM
2011
IEEE
14 years 7 months ago
Network-aware behavior clustering of Internet end hosts
Abstract—This paper explores the behavior similarity of Internet end hosts in the same network prefixes. We use bipartite graphs to model network traffic, and then construct on...
Kuai Xu, Feng Wang 0002, Lin Gu
ICIAP
2007
ACM
16 years 4 months ago
A Method of Clustering Combination Applied to Satellite Image Analysis
An algorithm for combining results of different clusterings is presented in this paper, the objective of which is to find groups of patterns which are common to all clusterings. T...
Ivan O. Kyrgyzov, Henri Maître, Marine Campe...
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 10 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin