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CIDM
2007
IEEE
14 years 2 months ago
Scalable Clustering for Large High-Dimensional Data Based on Data Summarization
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
EDBT
2004
ACM
192views Database» more  EDBT 2004»
14 years 8 months ago
LIMBO: Scalable Clustering of Categorical Data
Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
Periklis Andritsos, Panayiotis Tsaparas, Ren&eacut...
MDM
2009
Springer
141views Communications» more  MDM 2009»
14 years 3 months ago
Constructing Hierarchical Representations of Indoor Spaces
Indoor spaces pose many challenges for spatial information systems, amongst them appropriate spatial communication. Compared to typical outdoor spaces, indoor spaces are clustered...
Kai-Florian Richter, Stephan Winter, Urs-Jakob R&u...
VLDB
1999
ACM
224views Database» more  VLDB 1999»
14 years 24 days ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
FSKD
2007
Springer
161views Fuzzy Logic» more  FSKD 2007»
14 years 2 months ago
A KFCM-Based Fuzzy Classifier
A proposed KFCM-based fuzzy classifier was introduced. As for the process of constructing such classifier, firstly, the original sample space is mapped into a high dimensional fea...
Aimin Yang, Lingmin Jiang, Yongmei Zhou