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ICMCS
2006
IEEE
159views Multimedia» more  ICMCS 2006»
9 years 3 months ago
Improving Speaker Diarization by Cross EM Refinement
In this paper, we present a new speaker diarization system that improves the accuracy of traditional hierarchical clustering-based methods with little increase in computational co...
Huazhong Ning, Wei Xu, Yihong Gong, Thomas S. Huan...
PAKDD
2007
ACM
143views Data Mining» more  PAKDD 2007»
9 years 3 months ago
Clustering Ensembles Based on Normalized Edges
The co-association (CA) matrix was previously introduced to combine multiple partitions. In this paper, we analyze the CA matrix, and address its difference from the similarity ma...
Yan Li, Jian Yu, Pengwei Hao, Zhulin Li
KES
2007
Springer
9 years 3 months ago
A Hierarchical Clustering Method for Semantic Knowledge Bases
Abstract. This work presents a clustering method which can be applied to relational knowledge bases. Namely, it can be used to discover interesting groupings of semantically annota...
Nicola Fanizzi, Claudia d'Amato
CIDM
2007
IEEE
9 years 3 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...
WISE
2009
Springer
9 years 6 months ago
Formal Identification of Right-Grained Services for Service-Oriented Modeling
Identifying the right-grained services is important to lead the successful service orientation because it has a direct impact on two major goals: the composability of loosely-coupl...
Yukyong Kim, Kyung-Goo Doh
SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
9 years 6 months ago
Detecting Communities in Social Networks Using Max-Min Modularity.
Many datasets can be described in the form of graphs or networks where nodes in the graph represent entities and edges represent relationships between pairs of entities. A common ...
Jiyang Chen, Osmar R. Zaïane, Randy Goebel
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
9 years 9 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
KDD
2005
ACM
135views Data Mining» more  KDD 2005»
9 years 9 months ago
A hybrid unsupervised approach for document clustering
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Mihai Surdeanu, Jordi Turmo, Alicia Ageno
ICPR
2002
IEEE
9 years 10 months ago
Fast Hierarchical Clustering Based on Compressed Data
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Erendira Rendon, Ricardo Barandela
MICCAI
2009
Springer
9 years 10 months ago
Constructing a Dictionary of Human Brain Folding Patterns
Abstract. Brain imaging provides a wealth of information that computers can explore at a massive scale. Categorizing the patterns of the human cortex has been a challenging issue f...
Zhong Yi Sun, Matthieu Perrot, Alan Tucholka, Deni...
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