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CLEF
2010
Springer
15 years 8 months ago
MapReduce for Information Retrieval Evaluation: "Let's Quickly Test This on 12 TB of Data"
We propose to use MapReduce to quickly test new retrieval approaches on a cluster of machines by sequentially scanning all documents. We present a small case study in which we use ...
Djoerd Hiemstra, Claudia Hauff
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 8 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
16 years 4 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
186
Voted
ICPR
2008
IEEE
16 years 1 months ago
Incremental clustering via nonnegative matrix factorization
Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF`s batch nature necessitates recomputation of whole basis set for new samples...
Serhat Selcuk Bucak, Bilge Günsel
154
Voted
WEBI
2007
Springer
16 years 1 months ago
K-SVMeans: A Hybrid Clustering Algorithm for Multi-Type Interrelated Datasets
Identification of distinct clusters of documents in text collections has traditionally been addressed by making the assumption that the data instances can only be represented by ...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...