Database Paper Browser

Back to papers

Evaluating Clustering in Subspace Projections of High Dimensional Data

Summary: Systematic benchmark of subspace clustering in high-dimensional data. Evaluates paradigms under a common framework; addresses ground-truth absence, varied metrics, and cross-paradigm comparison; provides real/synthetic datasets and repeatable baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9917
Venue
VLDB
Year
2009
Pagerank
4.5701004e-05
Overall Rank
8,168 | 43.18%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers