TY - GEN
T1 - Scalable density-based subspace clustering
AU - Müller, Emmanuel
AU - Assent, Ira
AU - Günnemann, Stephan
AU - Seidl, Thomas
PY - 2011
Y1 - 2011
N2 - For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well.
AB - For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well.
KW - data mining
KW - density-based clustering
KW - high dimensional data
KW - scalability
KW - subspace clustering
UR - http://www.scopus.com/inward/record.url?scp=83055161713&partnerID=8YFLogxK
U2 - 10.1145/2063576.2063733
DO - 10.1145/2063576.2063733
M3 - Conference contribution
AN - SCOPUS:83055161713
SN - 9781450307178
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1077
EP - 1086
BT - CIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management
T2 - 20th ACM Conference on Information and Knowledge Management, CIKM'11
Y2 - 24 October 2011 through 28 October 2011
ER -