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ADBIS
2007
Springer
145views Database» more  ADBIS 2007»
14 years 12 days ago
A Method for Comparing Self-organizing Maps: Case Studies of Banking and Linguistic Data
The method of self-organizing maps (SOM) is a method of exploratory data analysis used for clustering and projecting multi-dimensional data into a lower-dimensional space to reveal...
Toomas Kirt, Ene Vainik, Leo Vohandu
WWW
2005
ACM
14 years 6 months ago
Clustering for probabilistic model estimation for CF
Based on the type of collaborative objects, a collaborative filtering (CF) system falls into one of two categories: item-based CF and user-based CF. Clustering is the basic idea i...
Qing Li, Byeong Man Kim, Sung-Hyon Myaeng
CEC
2005
IEEE
13 years 12 months ago
Multiobjective clustering around medoids
Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...
Julia Handl, Joshua D. Knowles
WISE
2009
Springer
14 years 3 months ago
Spectral Clustering in Social-Tagging Systems
Social tagging is an increasingly popular phenomenon with substantial impact on the way we perceive and understand the Web. For the many Web resources that are not self-descriptive...
Alexandros Nanopoulos, Hans-Henning Gabriel, Myra ...
BMCBI
2008
142views more  BMCBI 2008»
13 years 6 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu