TY - GEN
T1 - Incremental clustering via nonnegative matrix factorization
AU - Bucak, Serhat Selcuk
AU - Gunsel, Bilge
PY - 2008
Y1 - 2008
N2 - Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF̀s batch nature necessitates recomputation of whole basis set for new samples. Although NMF is a powerful content representation tool, this limits the use of NMF in online processing of large data sets. Another problem with NMF, like other partitional methods, is determining the actual number of clusters. Deciding the rank of the factorization is also critical since it has a significant effect on clustering performance. This paper introduces an NMF based incremental clustering algorithm which allows increasing number of clusters adaptively thus eliminates optimal rank selection problem. Test results obtained on large video data sets demonstrate that the proposed clustering scheme is capable of labeling linearly separable data as well as non-separable samples with a small false positive ratio.
AB - Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF̀s batch nature necessitates recomputation of whole basis set for new samples. Although NMF is a powerful content representation tool, this limits the use of NMF in online processing of large data sets. Another problem with NMF, like other partitional methods, is determining the actual number of clusters. Deciding the rank of the factorization is also critical since it has a significant effect on clustering performance. This paper introduces an NMF based incremental clustering algorithm which allows increasing number of clusters adaptively thus eliminates optimal rank selection problem. Test results obtained on large video data sets demonstrate that the proposed clustering scheme is capable of labeling linearly separable data as well as non-separable samples with a small false positive ratio.
UR - http://www.scopus.com/inward/record.url?scp=77957948984&partnerID=8YFLogxK
U2 - 10.1109/icpr.2008.4761104
DO - 10.1109/icpr.2008.4761104
M3 - Conference contribution
AN - SCOPUS:77957948984
SN - 9781424421756
T3 - Proceedings - International Conference on Pattern Recognition
BT - 2008 19th International Conference on Pattern Recognition, ICPR 2008
PB - Institute of Electrical and Electronics Engineers Inc.
ER -