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» Clustering the Feature Space
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CVPR
2005
IEEE
15 years 3 days ago
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
Kai Zhang, Ming Tang, James T. Kwok
SIGIR
2000
ACM
14 years 2 months ago
An investigation of linguistic features and clustering algorithms for topical document clustering
We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
SIGIR
2008
ACM
13 years 10 months ago
Knowledge transformation from word space to document space
In most IR clustering problems, we directly cluster the documents, working in the document space, using cosine similarity between documents as the similarity measure. In many real...
Tao Li, Chris H. Q. Ding, Yi Zhang 0005, Bo Shao
ISCA
1994
IEEE
104views Hardware» more  ISCA 1994»
14 years 2 months ago
Exploring the Design Space for a Shared-Cache Multiprocessor
In the near future, semiconductor technology will allow the integration of multiple processors on a chip or multichipmodule (MCM). In this paper we investigate the architecture an...
Basem A. Nayfeh, Kunle Olukotun
PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
14 years 1 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu