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ICASSP
2008
IEEE
15 years 5 months ago
Unsupervised language model adaptation via topic modeling based on named entity hypotheses
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
Yang Liu, Feifan Liu
BMCBI
2006
164views more  BMCBI 2006»
14 years 11 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
EDBT
2004
ACM
145views Database» more  EDBT 2004»
15 years 11 months ago
CUBE File: A File Structure for Hierarchically Clustered OLAP Cubes
Abstract. Hierarchical clustering has been proved an effective means for physically organizing large fact tables since it reduces significantly the I/O cost during ad hoc OLAP quer...
Nikos Karayannidis, Timos K. Sellis, Yannis Kouvar...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
15 years 11 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 3 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer